Fuzzy multicriteria disposal method and site selection for municipal solid waste

Assessment of healthcare waste treatment methods using an interval-valued intuitionistic fuzzy double normalization-based multiple aggregation approach

Healthcare waste management has been an extensively attractive topic recently since it is one of the key concerns regarding both environment and public health, predominantly in developing nations. The optimization of the treatment procedure for healthcare waste is indeed a complex "multi-criteria decision-making (MCDM)" problem that involves contradictory and interweaved critical criteria. To successfully handle this issue, this study extends the original method, named the "double normalization-based multi-aggregation (DNMA)" approach, with "interval-valued intuitionistic fuzzy sets (IVIFSs)" for decision-making problems taking criteria in terms of benefit or cost types. This method involves two target-based normalizations and three subordinate utility models. To estimate the criteria weights, we propose a new parametric divergence measure and discuss the feasibility of the developed divergence measure based on existing divergence measures for IVIFSs. Further, the developed framework is implemented to elucidate the "healthcare waste treatment (HCWT)" problem. The comparative and sensitivity analyses of the outcomes indicate that the proposed approach efficiently tackles the problem of HCWT selection. The outcomes show that steam sterilization (0.462) is the optimal one for HCWT. The prioritization options, obtained by presented approach, are dependable and suitable, which are steam sterilization ≻ microwave ≻ incineration ≻ landfilling.

Integration of LCSA and GIS-based MCDM for sustainable landfill site selection: a case study

The paper aims at developing a framework for decision-support to select a sustainable landfill site in Bardaskan City (Iran) by combining life cycle sustainability assessment (LCSA) concepts and geographic information system (GIS)-based multi-criteria decision-making (MCDM). Overall, 13 criteria were chosen (three constraints and 10 factors) and classified into three main aspects of sustainability (i.e., environmental, social, and economic) to achieve the research goals. Boolean and fuzzy logic were employed to standardize the classified constraints and factors, respectively. Analytic hierarchy process (AHP) was used to calculate the factors' weights and then suitability maps were produced using the GIS analysis. The layers were combined using simple additive weighting (SAW). Next, the most sustainable sites were obtained. The results indicated that distance from city backline, groundwater depth, and distance from rural areas were the most significant factors with the weight of 0.338, 0.141, and 0.129, respectively. The final map of suitable sites was created by classifying the SAW layer according to 75, 80, and 85% of suitability to show the high, medium, and low priority areas for landfill site selection, respectively. Therefore, integration of LCSA and GIS-based MCDM to select the sustainable landfill site for municipal solid waste (MSW) is highly important, which can be effectively employed in regional and urban planning to select the location of appropriate and sustainable landfills.

Development and application of a prioritization and rehabilitation decision support tool for uncontrolled waste disposal sites in developing countries

The uncontrolled dumping of solid waste is widespread in many developing countries with most of all generated wastes being indiscriminately disposed of in an unsanitary manner that entails significant environmental and public health risks. It is imperative to prioritize dumpsites based on their relative risks so that the necessary control and remedial measures can be undertaken. This research aimed to formulate a pragmatic prioritization and rehabilitation decision tool that can be utilized in low- and middle-income countries to guide decision makers in prioritizing dumpsites for remediation and in identifying the most suitable rehabilitation option for municipal as well as construction and demolition waste. The established prioritization model presents an integrated, risk-based approach to developing a decision-making tool for dumpsite prioritization and rehabilitation. The rehabilitation tool drew on a decision tree module to develop the appropriate remedial measures required for each site. The model proved to be effective in prioritizing uncontrolled solid waste disposal sites in Lebanon and for adopting control and remedial measures that can considerably improve decision-making. The improper disposal of solid waste adversely affects public health and the environment in, to a greater or lesser extent, almost all low- and middle-income countries. Considering that it is unfeasible to remediate all uncontrolled solid waste disposal sites at once, the proposed model facilitates the evaluation process by prioritizing sites for closure and remediation based on their relative risks. Integr Environ Assess Manag 2023;19:436-445. © 2022 SETAC.

Selection of plastic solid waste treatment technology based on cumulative prospect theory and fuzzy DEMATEL

Under the global implementation of a low-carbon economy, the treatment of municipal plastic solid waste (PSW) has become an important task to be solved urgently. In the actual decision-making process of PSW treatment, the evaluation information is usually fuzzy, and the decision-makers (DMs) are bounded rational. For selecting the most appropriate PSW treatment technology, we propose a multi-criteria decision-making (MCDM) method based on cumulative prospect theory and fuzzy decision-making trail and evaluation laboratory (DEMATEL). Firstly, we construct the criteria system of PSW treatment that consists of 9 sub-criteria from the perspectives of environment, economy, society, and technology. Then, considering the interdependences and interactions between these evaluation criteria and allowing multiple stakeholders to participate in decision-making, we propose a fuzzy DEMATEL method to deal with the fuzziness of evaluation in the decision-making process and determine the weights of the evaluation criteria. Subsequently, taking into account the different opinions of different stakeholders and psychological factors such as risk preference and loss aversion of stakeholders, we aggregate the evaluation information of different stakeholders and develop the PSW treatment alternatives to rank the orders by using the proposed multi-actor cumulative prospect theory (CPT) method. We study seven alternative processes for PSW treatment by the developed model, including landfill, recycling, pyrolysis, incineration, and the combination of landfilling and recycling, landfill and incineration, and recycling and pyrolysis. According to the ranking results, we find the combination of recycling and incineration is the best treatment alternative. We take the seven PSW treatment technologies in Shanghai as the case study to verify the effectiveness and feasibility of the proposed method. Through the sensitivity analysis and comparison analysis with fuzzy similarity to ideal solution (FTOPSIS) method and an acronym in Portuguese of the interactive and multi-criteria decision-making (TODIM) method, we illustrate the effectiveness and superiority of the proposed method. This research provides significant references for the PSW treatment technology selection problems under uncertain environments and extends the methods in the decision-making field.

Entropy and discrimination measures based q-rung orthopair fuzzy MULTIMOORA framework for selecting solid waste disposal method

Fastest growing population, rapid urbanization, and growth in the disciplines of science and technology cause continually development in the amount and diversity of solid waste. In modern world, evaluation of an appropriate solid waste disposal method (SWDM) can be referred as multi-criteria decision-making (MCDM) problem due to involvement of several conflicting quantitative and qualitative sustainability indicators. The imprecision and ambiguity are usually arisen in SWDM assessment problem, and the q-rung orthopair fuzzy set (q-ROFS) has been recognized as one of the adaptable and valuable ways to tackle the complex uncertain information arisen in realistic problems. In the context of q-ROFSs, entropy is a significant measure for depicting fuzziness and uncertain information of q-ROFS and the discrimination measure is generally used to quantify the distance between two q-ROFSs by evaluating the amount of their discrimination. Thus, the aim of this study is to propose a novel integrated framework based on multi-attribute multi-objective optimization with the ratio analysis (MULTIMOORA) method with q-rung orthopair fuzzy information (q-ROFI). In this approach, an integrated weighting process is presented by combining objective and subjective weights of criteria with q-ROFI. Inspired by the q-rung orthopair fuzzy entropy and discrimination measure, objective weights of criteria are estimated by entropy and discrimination measure-based model. Whereas, the subjective weights are derived based on aggregation operator and the score function under q-ROFS environment. In this respect, novel entropy and discrimination measure are proposed for q-ROFSs. Furthermore, to display the feasibility and usefulness of the introduced approach, a case study related to SWD method selection is presented under q-ROFS perspective. Finally, comparison and sensitivity investigation are presented to confirm the robustness and solidity of the introduced approach.

Application of ArcGIS and QFD-based model for site selection for bio-medical waste disposal

With the increasing formalisation of the health sector in India, the bio-medical waste (BMW) disposal regulations are getting stringent and its implementation is being enforced strictly. The coronavirus disease 2019 (COVID-19) created a healthcare crisis because of the highly contagious nature of the novel virus. Measures employed for the prevention and management of COVID-19 resulted in the generation of an unprecedented amount of BMW in Indian medical history. This BMW needs to be disposed of safely at a suitable site to prevent secondary infection and the potential spread of the virus in the environment. The selection of an appropriate site for BMW disposal requires comparing a wide range of social, economic and environmental factors corresponding to different site locations, which makes it a multi-criteria decision-making (MCDM) problem. This study aims to solve the BMW site selection problems using a quality function deployment-based model that can consider both the subjective and the objective criteria, and evaluate them as per the user's requirements. The proposed model is applied to evaluate the suitability of waste disposal sites in the city of Bilaspur in Chhattisgarh, India. At first, eight possible locations for BMW disposal are identified, while utilising geographical information system (GIS). Consequently, the developed model is applied to evaluate the identified sites, taking 18 relevant criteria into consideration. A software prototype is developed in Visual BASIC 6 to automate the entire decision-making process, further adding to the novelty of the work.

A novel hybrid multi-criteria group decision-making approach with intuitionistic fuzzy sets to design reverse supply chains for COVID-19 medical waste recycling channels

The COVID-19 pandemic has led to exponential growth in COVID-19 medical waste (CMW) generation worldwide. This tremendous growth in CMW is a major transmission medium for COVID-19 virus and thus brings serious challenges to medical waste (MW) management. Designing an efficient and reliable CMW reverse supply chain in this situation can help to prevent epidemic spread. Nowadays, the assessment of CMW recycling channels has become a challenging mission for health-care institutions, especially in developing countries. It can be seen as a complex multi-criteria group decision-making (MCGDM) problem that requires the consideration of multiple conflicting tangible and intangible criteria. Nevertheless, few academics have been concerned about this issue. Moreover, current MCGDM methods have limited support for CMW recycling channel evaluation and they do not consider hospitals' reverse supply chain strategy when evaluating. Thus, this study presents a novel MCGDM approach based on intuitionistic fuzzy sets (IFSs) and the VIKOR method for assessing the capacity of CWM recycling channels. According to the characteristics of CMW, processing flow and the TOE (Technology, Organization and Environment) theoretical framework, we established a new CMW recycling channel capacity evaluation index system which makes our proposed method more targeted and efficient. In the decision-making process, we integrate the best-worst method (BWM) and entropy to determine the decision makers (DMs) weighting in a more comprehensive way, considering both subjective and objective criteria, which was ignored by many MCGDM methods. A new aggregation operator called IFWA is proposed by us, considering the priority of DMs. Based on both the ranking of capacity and disposal charges, we then position the alternatives in the recycling channel priority index (RCPI) matrix constructed by us. According to this PCPI matrix and the reverse supply chain strategy of hospitals, a more reasonable CMW allocation strategy is determined and a more efficient CMW reverse supply chain is designed. Finally, a real case study from Wuhan was examined to illustrate the validation of our approach.

Optimal Waste-to-Energy Strategy Assisted by Fuzzy MCDM Model for Sustainable Solid Waste Management

In Vietnam, rapid population and economic growth are responsible for the recent increase in solid waste. Energy production from waste is now becoming an effective solution around the world, especially in Vietnam, to solve environmental challenges while contributing to the country’s sustainable energy production. Waste-to-energy production has become a solution to the municipal solid waste problem, which is projected to increase by 10–16%. In this study, the author proposed a fuzzy MCDM model to assess and select a solid-waste-to-energy plant location in Vietnam. In the first stage, the fuzzy analytic hierarchy process (FAHP) technique is utilized to analyze the relative weight of the primary and secondary evaluation elements, and a combined compromise solution (CoCoSo) model is used to rank the candidates in the final stage. This is the first solid-waste-to-energy plant location evaluation and selection model used in a renewable energy project in Vietnam based on expert interviews and a literature review. This study’s contribution can be a significant guide in analyzing and selecting appropriate locations for solid-waste-to-energy projects, as well as for decision makers and investors in other renewable energy projects in Vietnam and throughout the world.

A GIS-based multi-criteria fuzzy approach to select a suitable location for a MSW-based power plant and landfill: a case study, Khuzestan province, Iran

The aim of this study was to find the best location for municipal solid waste (MSW)-based power plant and landfill. Another goal was to investigate the energy recovery potential of MSW by anaerobic digestion and recycling process. A combination of multi-criteria fuzzy decision making system was applied in GIS environment to select the most suitable site for MSW-based power plant and landfill. The effective sub-criteria were classified into three main categories of environmental, social, and economic criteria, and fuzzy analytic hierarchy process was used to weight and integrate them. The method was used in a case study to find the best location of MSW-based plant and landfill in Khuzestan province, Iran. Based on the amount of MSW production in this province and as a result, the potential for energy savings by recycling the recyclable part and recovering energy from the digestible part, the amount of fossil fuel that can be saved and the emission of greenhouse gases that can be avoided were estimated. Based on the results, in total, recycling the recyclable portion (dry waste) and producing energy from the digestible portion (wet waste) of MSW in Khuzestan province, leads to avoid burning 7.4 billion MJ of fossil fuels and emitting 644,169 t of CO₂eq GHG. The results also showed that the integration of fuzzy logic and multi-criteria fuzzy decision making system provides more flexibility in choosing the best location for the MSW-based plant. This method is flexible enough and in other situations can include other necessary criteria and can provide a comprehensive guideline for decision makers in choosing the optimal location for a power plant or a landfill.

Odor-aided analysis for landfill site selection: study of DOKAP Region, Turkey

In our world, with the increase of factors such as the rapid and irresponsible consumption of natural resources, man-made environmental disasters, global warming, and pollution of water resources in our world, the need for more efficient storage and disposal of solid waste has arisen. The presentation of the data required to solve spatial problems such as storage, management, and location selection can be carried out extensively and effectively using geographic information systems (GIS). On the other hand, the unsatisfactory results obtained with GIS recently have made it mandatory to use spatial multiple criteria decision-making (S-MCDM) methods that include the decision-makers in the process. In this study, landfill site selection was carried out in eight provinces in the region under the responsibility of the Eastern Black Sea Project Regional Development Administration (DOKAP). GIS and S-MCDM were used together in this site selection process. A total of eight spatial data layers were used in the site selection application. Afterwards, storage areas determined as suitable via GIS analysis underwent additional evaluation, taking into account geological, seismic, and environmental factors as well as transportation costs. In addition to these multi-component evaluations, odor analyses were carried out on the proposed storage areas using the prevailing wind direction.

Comprehensive solid waste dumpsite selection in arid cities of Northeastern Ethiopia: A spatial-MCDA approach

In the coming three decades, world waste will be expected to increase by 70%. Coupled with the absence of waste management technologies, unregulated dumping remained a threat to sustainable development in developing countries. To this end, this study emphasized to trace socially acceptable and environmentally friendly solid waste dumpsite for the northeastern arid cities of Ethiopia. The tuneful integration of GIS and MCDA was used for the end-to-end processing of 17 variables. At the earlier, to increase alternative dumpsites and seeking for safe zone outside the cities, 20 km buffer at Semera-logia city was used as a spatial scope of the study. Fifteen key informants (KIs) from related departments of the city and Samara University were selected to validate the model result. In the end, Ordinal Regression (OR) analysis was used to test the significance of the criteria's on suitable dumpsite selection. The pair-wise comparison matrix shows that variables such as distance from surface water (11.32%), distance from the settlement (9.88%), distance from boreholes (8.87%), and aquifer productivity (8.51%) were the top weighed criteria for the study area. The weighted overlay result shows that 10.75% and 38.64% of the study area are found to be convenient and prohibited for dumping, respectively. Indeed, the KIs were agreed on 77% of the validation points and the agreement decreases from points of not-suitable to highly suitable. Except for aquifer productivity, all the 16 variables are significantly and negatively affect dumpsites suitability. This result can be further used as a preliminary database for experts to design landfill structures and also management operations for decision-makers.Implications: The identification of potential dumpsite is an important step towards maximizing efficiency and building sustainability in the arid areas. The decision-making process shall be based on the empirical investigation. The decision-making process on dumpsite selection were well thought out both the socio-economic and environmental factors. In owing process, the empirical investigation that was conducted focusing on socio-economic dimension jeopardized other components of the environments. The approach that considers both socio-economic and spatial factors was all-inclusive. Overall, decision-makers could have a good insight to work on prioritizing dumpsite alternatives and implement feasible waste management actions.

A GIS-based multi-criteria decision-making method for the selection of potential municipal solid waste disposal sites in Mersin, Turkey

Due to rapid urbanization and the resulting rapid population increases, an important problem for cities today is the elimination of solid waste or finding suitable places for waste storage. Municipal solid waste disposal (MSWD) site selection is one of the most important steps in urban waste management. Many criteria political, economic, social, and technological should be considered in this process. Geographic information systems (GIS) and multi-criteria decision-making (MCDM) are tools that are superior to traditional methods in the planning phase of site selection studies. In this study, suitable MSWD sites were determined in Mersin (a Turkish province) based on GIS and the analytic hierarchy process, an MCDM method. Unsuitable areas in the study were removed at the beginning of the analysis. Eleven evaluation criteria were selected: elevation, slope, permeability, distance from lineaments, groundwater level, distance from rivers and water surfaces, distance from roads, distance from settlements, distance from protected areas, and land cover. Considering the evaluation and exclusion criteria, 19.12% of the study area was deemed suitable, and 80.88% was determined unsuitable for an MSWD site. An MSWD suitability map was created as a result of the study. The outcomes indicate that 80,377 ha and 83,022 ha of the study area were classified as high and very high suitability, respectively. Based on these results, we evaluate whether the locations of existing solid waste landfills are appropriate and propose alternative solid waste landfills for each district.

Waste to energy spatial suitability analysis using hybrid multi-criteria machine learning approach

Municipal solid waste is typically managed in developing countries through various disposal methods, such as sanitary landfills or dumpsites. Alternatively, waste to energy (WTE) systems have been recently adopted to provide sustainable waste management and diversify the energy mix. The abundance of remotely sensed datasets and derivatives, along with the rapid development of artificial intelligence, can offer an effective solution for WTE site selection. In this study, an analytical hierarchy process (AHP)-based framework supported by multiple machine learning algorithms (gradient boosted tree (GBT), decision tree (DT), and support vector machines (SVMs)) was established to explore the optimum location for WTE facilities. Various social, legal, environmental, economic, morphological, and land cover parameters were considered under 11 thematic geospatial raster layers. The proposed framework was applied to the 1.5-million-capita city of Sharjah, United Arab Emirates. A novel approach was developed to incorporate Gaussian dispersion modeling for the expected air pollution emissions from a WTE facility. The results showed that the accuracy performance sequence of the algorithms was 94.6, 93.9, and 91.8% for GBT, DT, and SVM, respectively. It was found that the distance from existing landfills had the most critical impact on the optimum location of the WTE facility, followed by the distance from coastline and elevation. The AHP consistency check revealed an acceptable overall criteria consistency index and the ratio of 0.0344 and 0.019, respectively. The results showed that 16.6% of Sharjah was considered extremely highly suitable areas. This research supports decision-makers in developing local guidelines for siting WTE facilities and determining the most suitable locations for such projects.

Waste disposal location selection by using pythagorean fuzzy REGIME method

The REGIME method is an easy to understand techniques which is based on pairwise comparisons and which can use qualitative data for decision making problems. The steps of the technique are simple and can be easily adopted to complex decision problems. Classical REGIME techniques use crisp numbers to evaluate qualitative evaluations. In this paper we propose Pythagorean Fuzzy REGIME (PF-REGIME) techniques which integrates Pythagorean Fuzzy Sets with REGIME technique. The proposed PF-REGIME is applied to waste disposal site selection problem. The decision model is constructed for three alternatives and five criteria in order to demonstrate the performance of the proposed PF-REGIME method.

Insights for Landfill Site Selection Using GIS: A Case Study in the Tanjero River Basin, Kurdistan Region, Iraq

The increasing world population and the growing quantity of solid waste have become a challenging problem facing governments and policy makers because of the scarcity of suitable sites for new landfills and the negative perception of these sites by the people. This study aims to evaluate the performance of different Multi-Criteria Decision-Analysis (MCDA) approaches using remote sensing and Geographic Information System (GIS) data for identifying suitable landfill sites (LFSs). We evaluated the methodologies used by various investigators and selected appropriate ones as suitable sites for Municipal Solid Waste (MSW) landfill in the Tanjero River Basin (TRB) in the Iraqi Kurdistan region. We applied Boolean Overlay (BO), Weighted Sum Method (WSM), Weighted Product Method (WPM), Analytic Hierarchy Process (AHP), and Technique for Order Performance by Similarity to an Ideal Solution (TOPSIS) to allow combined use of 15 thematic layers as predictive factors (PFs). In this study, we applied the Topographic Position Index (TPI) for the first time to select MSW LFSs. Almost all methods showed reliable results and we identified eight suitable sites situated in the western part of the TRB having total area of ~18.35 km2. The best accuracy was achieved using the AHP approach. This paper emphasizes that the approach of the used method is useful for selecting LFSs in other areas, which are located in similar environments.

Landfill Site Selection Using GIS Based Multicriteria Evaluation Technique in Harar City, Eastern Ethiopia

Solid waste disposal is one of the challenging components in integrated solid waste management. Particularly the problem is prominent in cities with rapid population growth and waste generation. Harar, a capital city of Harari regional state located in the eastern part of Ethiopia, covers an area of 19.5 km² and has a total population of 270 000. Despite the fastest population growth of the city, it doesn't have a landfill site to accommodate the waste generated and open dumping is in full practice. As an integral part of a solid waste management plan, the construction of a landfill has been suggested by the city municipality. However, the multi-dimensional and conflicting aspect of landfill sitting, which involves environmental, social, technical, and economic considerations, challenges the location of a suitable landfill site. In the current study, we have applied geographic information system (GIS) and analytical hierarchy process (AHP) multi-criteria decision analysis to select a landfill site through minimizing conflicting interests. Environmental and socio-economic factors including well water, distance from residence, land use and land cover, elevation, slope, and wind direction were weighted to develop a suitability index for landfill siting. Experts' opinion was obtained to rank the aforementioned factors. The required landfill size was determined based on population growth, waste generation rate, and waste volume/year. Accordingly, the suitability index resulted in 3% of the area as highly suitable, and the rest 0.29%, 14.18%, 52.75%, and 29.8% classified as unsuitable, least suitable, moderately suitable, and suitable, respectively. Considering the future trend of waste generation, 16 ha of land located in the eastern part of the city was selected as a candidate landfill site with all the required suitability. The results of this study can be used as an input for decision making in siting landfill for Harar city.

Multi-criteria healthcare waste disposal location selection based on Fermatean fuzzy WASPAS method

Medical services inevitably generate healthcare waste (HCW) that may become hazardous to healthcare staffs, patients, the population, and the atmosphere. In most of the developing countries, HCW disposal management has become one of the fastest-growing challenges for urban municipalities and healthcare providers. Determining the location for HCW disposal centers is a relatively complex process due to the involvement of various alternatives, criteria, and strict government guidelines about the disposal of HCW. The objective of the paper is to introduce the WASPAS (weighted aggregated sum product assessment) method with Fermatean fuzzy sets (FFSs) for the HCW disposal location selection problem. This method combines the score function, entropy measure, and classical WASPAS approach within FFSs context. Next, a combined procedure using entropy and score function is proposed to estimate the criteria weights. To do this, a novel score function with its desirable properties and some entropy measures are introduced under the FFSs context. Further, an illustrative case study of the HCW disposal location selection problem on FFSs is established, which evidences the practicality and efficacy of the developed approach. Comparative discussion and sensitivity analysis are made to monitor the permanence of the introduced framework. The final results approve that the proposed methodology can effectively handle the ambiguity and inaccuracy in the decision-making procedure of HCW disposal location selection.

A Framework to Evaluate Project Complexity Using the Fuzzy TOPSIS Method

This work aims to help managers anticipate, detect, and keep under control complex situations before facing negative consequences. This article explores complexity modeling theory and develops a framework and associated score sheet to measure project complexity. A framework comprising ninety factors is presented and divided into seven categories: stakeholders, project team, project governance, product, project characteristics, resources, and environment. For the project complexity assessment grid, the project manager prioritizes and weighs its factors using linguistic variables. The score sheet is customizable in its handling of the factors and their weights. A critical state of the art on multi-criteria methodologies is presented, as well as reasons for using the fuzzy technique for order preference by similarity to ideal solution (TOPSIS) method. This method provides early-warning signs with the possibility of comparing multiple projects. It also enables one to measure and prioritize areas and domains where complexity may have the highest impact. Practical applications on three projects within an automotive manufacturer highlight the benefits of such an approach for managers. Project managers could use both a project complexity rating system and a measure of risk criticality to decide on the level of proactive actions needed. This research work differs from traditional approaches that have linked proactive actions to risk criticality but not project complexity.

A multi-attribute decision-making-based site selection assessment algorithm for garbage disposal plant using interval q-rung orthopair fuzzy power Muirhead mean operator

With the increase of the global population and the improvement of people's living standards, the output of garbage generated by human activities is also increasing day by day. Choosing an appropriate garbage disposal site is one of the key links for the harmless disposal of garbage. However, due to the uncertainty and complexity of socio-economic development and the limited cognitive ability of decision-makers, how to rationally select the garbage disposal site has become a challenging task. This study drew a new multi-attribute decision-making method based on interval q-rung orthopair fuzzy weighted power Muirhead mean (Iq-ROFPWMM) operator to evaluate site selection scheme of garbage disposal plant, and support for garbage disposal site selection. In this method, firstly, power average and Muirhead mean operators are integrated and introduced into the interval q-rung orthopair fuzzy environment to construct an Iq-ROFPWMM operator. Meanwhile, some properties of idempotence, boundedness and monotonicity for the Iq-ROFPWMM operator are analyzed. Then, a multi-attribute decision-making method using Iq-ROFPWMM operator is established. After that, a practical case on the evaluation of garbage disposal site selection scheme is given to verify the effectiveness of the proposed method. Further, parameter analysis and comparative analysis are applied to demonstrate the superiority of our method. The results show that this method boasts wider space for evaluation information representation, more flexible adaptation to the environment evaluation, and stronger robustness of the evaluation results. Finally, some conclusions of this study are drawn and the development direction is revealed.

Geospatial Insights for Retail Recommendation Using Similarity Measures

Recommending a retail business given a particular location of interest is nontrivial. Such a recommendation process requires careful study of demographics, trade area characteristics, sales performance, traffic, and environmental features. It is not only human effort taxing but often introduces inconsistency due to subjectivity in expert opinions. The process becomes more challenging when no sales data can be used to make a recommendation. As an attempt to overcome the challenges, this study used the machine learning approach that utilizes similarity measures to perform the recommendation. However, two challenges required careful attention when using the machine learning approach: (1) how to prepare a feature set that can commonly represent different types of retail business and (2) which similarity measure approach produces optimal recommendation accuracy? The data sets used in this study consist of points of interest, population, property, job type, and education level. Empirical studies were conducted to investigate (1) the overall accuracy of proposed similarity measure approaches to the retail business recommendation, and (2) whether the proposed approaches have a bias toward certain retail categories. In summary, the findings suggested that the proposed similarity-based techniques elicited an accuracy of above 70% and demonstrated higher accuracy when the recommendation was made within a set of similar retail businesses.

Landfill site selection using multi criteria decision making: Influential factors for comparing locations

Although a lot of research has focused on energy recovery and recycling of valuable materials from wastes to reduce loads on landfills, landfilling is still an inseparable part of solid waste management. Since landfills potentially pose a risk to human health and the surrounding environment, landfill site selection is an important endeavor that has to be carried out with great care. Choosing a suitable location for landfills depends on several factors and is a complicated procedure. In this paper, a comprehensive review of landfill site selection methods, with an emphasis on multi criteria decision making (multiple criteria decision analysis) has been presented. Assessments indicate that the most frequently used methods are weighted linear combination (WLC), ordered weighted averaging (OWA), analytic hierarchy process (AHP), fuzzy analytic hierarchy process (F-AHP), TODIM, fuzzy TODIM, analytic network process (ANP), fuzzy-analytic network process (F-ANP), and grey systems theory, each of which is discussed. The most widely used factors for selecting a landfill site are groundwater depth, surface water vicinity, elevation, land slope, soil permeability, soil stability, flooding susceptibility, lithology and stratification, faults, land use type, nearby settlements and urbanization, cultural and protected site vicinity, wind direction, roads, railways, proximity to building materials, pipelines and powerlines, and proximity to airports.

Considering environmental variables in the design of waste dumpsites

Mining generates a significant quantity of waste material including ballast, gravel, and slags, which are often deposited in areas without taking into account the environment impacts and the need to ensure the physical and chemical stability of the disposed waste. One of the less studied problems is the emission of particulate matter produced by wind erosion at the dumpsites. This erosion is mainly caused by two factors, wind speed and turbulence, due to surface phenomenon. Until now, the design of waste dumpsites in the Chilean mining industry has not considered these environmental conditions. Efforts to minimize disposal costs have always been achieved by depositing ballast without considering these variables. When wind impacts this unprotected surface, it creates a source of dust that requires some special attention. The problem that this research tries to solve is to reduce particulate material to the atmosphere from waste dumps in which, under certain atmospherics and geographic conditions, specifically on winter season, its concentrations overpass the maximum limit allowed by law, generating bronchopulmonary diseases and even closing partially or totally mine operation. The result is the creation of a waste dumpsite design model, with its corresponding algorithms, which will allow optimization of the waste dumpsite design. From these results, future researches could explore more sustainable mining, such as unit operations, drilling, blasting, load and crushing material, reducing particulate material emissions to the atmosphere, and minimizing environmental impact due to exploitation.

Selection of MSW landfill site by fuzzy-AHP approach combined with GIS: case study in Ahvaz, Iran

The study was aimed to use fuzzy multi-criteria decision making integrated with GIS to select the optimum location for municipal solid waste (MSW) landfill sites that comply with standard landfill guidelines and environmental and socio-economic criteria. Fuzzy logic and, in particular, fuzzy sets were applied to create the criteria layers in GIS and to weigh and integrate these layers in GIS. Analytical Hierarchy Process (AHP) was also used to determine the land suitability for landfill. The method was used as a case study to determine the location of landfills in the suburbs of Ahvaz, Iran. According to the results, transportation networks and residential and commercial areas were the most influential factors on the placement of landfills, with a final weight of 0.163 and 0.131, respectively. Areas near roads and transportation networks but far from the sensitive environmental zones were most suitable for landfill. Finally, 11 sites that met the defined requirements were selected as suitable locations for MSW landfill. This technique and its results can provide a proper guideline to help decision makers choose the optimal landfill site in the future. Depending on their importance in each region, the methodology can incorporate other factors and criteria.

Implementation of fuzzy, Simos and strengths, weaknesses, opportunities and threats analysis for municipal solid waste landfill site selection: Adana City case study

The selection of suitable landfill locations for municipal solid waste has become a top priority, especially in developed countries as a result of rapid population growth, unplanned urbanisation, increasing waste production and the limited area available. However, determining the location of landfill sites is a complex decision-making problem for municipalities and depends on social, environmental, technical and economic factors and regulations. In this study, we combined a geographic information system (GIS), multi-criteria decision-analysis techniques and fuzzy logic to determine the best location for landfill sites in Adana, Turkey, in four steps. Firstly, the threshold values and the coefficient weights of 15 criteria, grouped into environmental and socio-economic factors, were determined by a literature review and expert opinion to select suitable landfill locations. Secondly, selection criteria were standardised using fuzzy logic. Thirdly, we assessed the criteria weights based on their effectiveness on the selection of potential landfill sites using the Simos method. According to the weight coefficients, environmental factors are more important than socio-economic factors. Final maps for each criterion were calculated and overlaid by a GIS. As a result, the final suitability results were divided into four discrete categories: very high, high, moderate and low suitability areas, representing 1%, 76%, 17% and 6% of the location options, respectively. Finally, four different alternative areas were identified as being very highly suitable for landfill locations, which were evaluated in detail using a strengths, weaknesses, opportunities and threats analysis. Three key aspects affect the final decision of a landfill site, in decreasing order of importance: environmental protection, minimising the negative impact on urban life quality and economic issues. Consequently, these results can guide decision-makers (ministries, municipalities, planners, etc.) during the selection of suitable landfill sites in both national and international studies.

GIS-Based Modeling for Selection of Dam Sites in the Kurdistan Region, Iraq

Iraq, a country in the Middle East, has suffered severe drought events in the past two decades due to a significant decrease in annual precipitation. Water storage by building dams can mitigate drought impacts and assure water supply. This study was designed to identify suitable sites to build new dams within the Al-Khabur River Basin (KhRB). Both the fuzzy analytic hierarchy process (AHP) and the weighted sum method (WSM) were used and compared to select suitable dam sites. A total of 14 layers were used as input dataset (i.e., lithology, tectonic zones, distance to active faults, distance to lineaments, soil type, land cover, hypsometry, slope gradient, average precipitation, stream width, Curve Number Grid, distance to major roads, distance to towns and cities, and distance to villages). Landsat-8/Operational Land Imager (OLI) and QuickBird optical images were used in the study. Three types of accuracies were tested: overall, suitable pixels by number, and suitable pixels by weight. Based on these criteria, we determined that 11 sites are suitable for locating dams for runoff harvesting. Results were compared to the location of 21 preselected dams proposed by the Ministry of Agricultural and Water Resources (MAWR). Three of these dam sites coincide with those proposed by the MAWR. The overall accuracies of the 11 dams ranged between 76.2% and 91.8%. The two most suitable dam sites are located in the center of the study area, with favorable geology, adequate storage capacity, and in close proximity to the population centers. Of the two selection methods, the AHP method performed better as its overall accuracy is greater than that of the WSM. We argue that when stream discharge data are not available, use of high spatial resolution QuickBird imageries to determine stream width for discharge estimation is acceptable and can be used for preliminary dam site selection. The study offers a valuable and relatively inexpensive tool to decision-makers for eliminating sites having severe limitations (less suitable sites) and focusing on those with the least restriction (more suitable sites) for dam construction.

Selecting Demolition Waste Materials Disposal Alternatives Using Fuzzy TOPSIS Technique

This article describes how in developing countries, millions of tons of construction and demolition wastes (CDWs) are lost every year due to lack of knowledge of recycling significance and/or procedures. Despite the high value of CDWs, high percentage of this waste is either dumped illegally or disposed in the landfills. Disposal methods should consider saving natural resources and maintaining the environmental conditions through maximizing the value of CDWs. This article aims at choosing the most sustainable disposal alternative using Multi-Criteria Decision Making (MCDM) Process, considering several sustainability measure indicators. The research introduces a list containing the most relevant and significant sustainable indicators that affect the selection of alternative for disposal of CDWs. Then, fuzzy TOPSIS technique is applied considering the significant indicators on each alternative to rank and choose the best alternative for disposal of CDWs.

Selecting Demolition Waste Materials Disposal Alternatives Using Fuzzy TOPSIS Technique

This article describes how in developing countries, millions of tons of construction and demolition wastes (CDWs) are lost every year due to lack of knowledge of recycling significance and/or procedures. Despite the high value of CDWs, high percentage of this waste is either dumped illegally or disposed in the landfills. Disposal methods should consider saving natural resources and maintaining the environmental conditions through maximizing the value of CDWs. This article aims at choosing the most sustainable disposal alternative using Multi-Criteria Decision Making (MCDM) Process, considering several sustainability measure indicators. The research introduces a list containing the most relevant and significant sustainable indicators that affect the selection of alternative for disposal of CDWs. Then, fuzzy TOPSIS technique is applied considering the significant indicators on each alternative to rank and choose the best alternative for disposal of CDWs.

Supporting Europe’s Energy Policy Towards a Decarbonised Energy System: A Comparative Assessment

The European Union (EU) aims to prepare its strategy and infrastructure for further decarbonisation of its energy system in the longer term towards 2050. Recent political discussions and research interest focus on ways to accelerate the development and deployment of low-carbon technologies with respect to the targets set for 2030 and 2050. However, the diverse options available that are to be implemented, are policy sensitive and need careful comparative assessment. This paper presents a multi-criteria approach based on an extension of the Preference Ranking Organization METHod for Enrichment of Evaluations (PROMETHEE) method for group decision-making that incorporates fuzzy set theory in order to evaluate alternative transformation pathways for achieving a sustainable energy system in EU. This assessment aims at providing a direction towards a most preferable pathway concept that should be taken into account by a future model-based analysis of the necessary transformation of our energy sector. The results obtained could support policymakers in drawing effective recommendations based on the findings. The added value of this analysis to policymakers is its contribution to plan climate and energy strategies towards a low-carbon transition pathway by using the information of this approach and prioritizing uncertainties through an environmental and energy perspective.

Storing E-waste in Green Infrastructure to Reduce Perceived Value Loss through Landfill Siting and Landscaping: A Case Study in Nanjing, China

Electronic waste (e-waste) represents a severe global environmental issue due to the fast upgrading and updating of electronic products and the high environmental risk. Current low recycling technology, high economic cost, and weak disposal capability make it difficult for e-waste to be rendered 100% harmless. E-waste disposal requires new site-selection methods and site-saving technology to take into account the loss of public perceived value. This study attempts to improve e-waste disposal through siting and landscaping to reduce perceived value loss. The first step is to determine the minimum distance for landfill siting by surveying the minimum loss of perceived value and to use the geographic information system (GIS) to sketch the suitable landfill site thereafter. To optimize the landfill landscape, a landscape infrastructure and its filling process have been designed to reduce the environmental risk and ensure future reuse potential. The application case showed that the minimum distance is 521 m, which was sensitive to the educational level and occupation of residents. The key to landfill landscaping is the construction of isolation layers and the integration of the landfill and urban landscape. The method described in this paper is characterized by minimizing the perceived loss of value to the public, reducing environmental risks, and preserving the resource value of e-waste. This design could provide an alternative to current electronic waste processing methods.

A system dynamics modeling to evaluate flooding impacts on municipal solid waste management services

The municipal solid waste management service system has been one of the most important service provisions in the city. Complex linkages within the system are impacted by waste quantities and qualities. Due to the complex characteristic of stock and flow in a waste management system, it is difficult to design a sustainable management system that can handle varying conditions, particularly in case of a disaster. Interferences from the natural disaster i.e. flooding could potentially affect the entire MSWM system. Flooding is a major disaster in many regions of the world and poses a challenge as an external disturbance to any part of the waste management system. This research has applied the concept of system dynamics (SD) to understand patterns and evaluate flood impacts on the waste management systems of 22 districts that transport waste to the Nongkhaem transfer station in Bangkok, Thailand. The SD model of waste management illustrates waste generation trends and collection and transfer patterns to predict potential flood-affected areas. The research analyzed different flooding hazard scenarios and evaluated potential impacts within flood-prone areas. The results proved that flooding has various degree of impacts on the accumulated waste amounts of services areas within and outside the flooded areas. The findings can be a guideline to help prepare an appropriate mitigation plan for waste management under flood conditions.

A Practical Approach to Reduce Greenhouse Gas Emissions from Open Dumps through Infrastructure Restructuring: A Case Study in Nanjing City, China

A new environmental ban has forced the restructure of open dumps in China since 1 July 2011. A technical process was established in this study that is feasible for the upgrade of open dumps through restructuring. The feasibility of restructuring and the benefit of greenhouse gas emission reductions were assessed according to field surveys of five landfills and four dumps in Nanjing. The results showed that the daily processing capacities of the existing landfills have been unable to meet the growth of municipal solid waste (MSW), making restructuring of the landfills imperative. According to an assessment of the technical process, only four sites in Nanjing were suitable for upgrading. Restructuring the Jiaozishan landfill effectively reduced the leachate generation rate by 5.84% under its scale when expanded by 60.7% in 2015. CO2 emissions were reduced by approximately 55,000–86,000 tons per year, in which biogas power generation replaced fossil fuels Fossil fuels accounted for the largest proportion, up to 45,000–60,000 tons. Photovoltaic power generation on the overlying land has not only reduced CO2 emissions to 26,000–30,000 tons per year but has also brought in continuing income from the sale of electricity. The funds are essential for developing countries such as China, which lack long-term financial support for landfill management after closure.

Improving the food waste composting facilities site selection for sustainable development using a hybrid modified MADM model

With the growth of population and the development of urbanization, waste management has always been a critical global issue. Recently, more and more countries have found that food waste constitutes the majority of municipal waste, if they are disposed of properly, will bring more benefits in sustainable development. Regarding the issue of selecting and improving the location to make the disposal facility towards achieving the aspiration level for sustainable development, since it involves multiple and complicated interaction factors about environment, society, and economy which have to be considered properly in the decision-making process of mutual influence relationship. It is basically a multiple attribute decision making (MADM) issue, a difficult problem which has been obsessing the governments of many countries is widely studied and discussed. This study uses the new hybrid modified MADM model, as follows, first to build an influential network relation map (INRM) via DEMATEL technique, next to confirm the influential weightings via DANP (DEMATEL-based ANP), and then to construct a decision-making model via a hybrid modified VIKOR method to improve and select the location for remaining the best disposal facilities. Finally, an empirical case study is illustrated to demonstrate that the proposed model can be effective and useful. In finding the process of decision making, environmental pollution is the main concern of many people in the area, but actually it is the resistance by the general public that has to be considered with first priority.

Geospatial Analytics in Retail Site Selection and Sales Prediction

Studies have shown that certain features from geography, demography, trade area, and environment can play a vital role in retail site selection, largely due to the impact they asserted on retail performance. Although the relevant features could be elicited by domain experts, determining the optimal feature set can be intractable and labor-intensive exercise. The challenges center around (1) how to determine features that are important to a particular retail business and (2) how to estimate retail sales performance given a new location? The challenges become apparent when the features vary across time. In this light, this study proposed a nonintervening approach by employing feature selection algorithms and subsequently sales prediction through similarity-based methods. The results of prediction were validated by domain experts. In this study, data sets from different sources were transformed and aggregated before an analytics data set that is ready for analysis purpose could be obtained. The data sets included data about feature location, population count, property type, education status, and monthly sales from 96 branches of a telecommunication company in Malaysia. The finding suggested that (1) optimal retail performance can only be achieved through fulfillment of specific location features together with the surrounding trade area characteristics and (2) similarity-based method can provide solution to retail sales prediction.

Prevention of landfill pollution by multicriteria spatial decision support systems (MC-SDSS): development, implementation, and case study

Landfilling of municipal solid waste (MSW) is one of the serious environmental concerns as improper location of MSW landfill site can release the pollutants into the surrounding environment. The process of selecting MSW landfill site is a complicated decision making problem since it is subjected to simultaneous assessment of several environmental criteria, rules, and restrictions besides sociocultural and economic ones. The current study suggests a framework based on Multicriteria spatial decision support systems (MC-SDSS) to select landfill site. The MC-SDSS is an advanced method to integrate multiple criteria decision analysis (MCDA) and geographical information systems (GIS) techniques. This approach enables the incorporation of several conflicting objectives and preferences into spatial decision models. In this study, 14 criteria were chosen and then divided into environmental, sociocultural, and economic categories. Finally, suitability maps were generated based on the MC-SDSS analysis. The developed method was implemented in a real case study in Arak city in northwestern region of Iran, which is environmentally sensitive area. The suitability maps of the case study in Arak showed that 10% (391 km²) is least suitable area, 23% (942 km²) is low suitable, 37% (1507 km²) is moderate suitable, 19% (783 km²) is suitable, and 11% (489 km²) is most suitable locations for landfill site, and finally, three best alternative sites were introduced for the final landfill site.

Macro and micro geo-spatial environment consideration for landfill site selection in Sharjah, United Arab Emirates

Waste management involves various procedures and resources for proper handling of waste materials in compliance with health codes and environmental regulations. Landfills are one of the oldest, most convenient, and cheapest methods to deposit waste. However, landfill utilization involves social, environmental, geotechnical, cost, and restrictive regulation considerations. For instance, landfills are considered a source of hazardous air pollutants that can cause health and environmental problems related to landfill gas and non-methanic organic compounds. The increasing number of sensors and availability of remotely sensed images along with rapid development of spatial technology are helping with effective landfill site selection. The present study used fuzzy membership and the analytical hierarchy process (AHP) in a geo-spatial environment for landfill site selection in the city of Sharjah, United Arab Emirates. Macro- and micro-level factors were considered; the macro-level contained social and economic factors, while the micro-level accounted for geo-environmental factors. The weighted spatial layers were combined to generate landfill suitability and overall suitability index maps. Sensitivity analysis was then carried out to rectify initial theoretical weights. The results showed that 30.25% of the study area had a high suitability index for landfill sites in the Sharjah, and the most suitable site was selected based on weighted factors. The developed fuzzy-AHP methodology can be applied in neighboring regions with similar geo-natural conditions.

Assessment of safety culture among job positions in high-rise construction: a hybrid fuzzy multi criteria decision-making (FMCDM) approach

The construction industry is known as one of the most dangerous industries, which not only requires sound operation of executive laws and regulations, but also necessitates the safety culture of all workers at workshops. Therefore, the aim of this research is to identify the factors of safety culture and ranking occupations in jobsites based on those factors in order to proactively improve the safety culture of construction projects and subsequently promote safety conditions and worksites. In this study, safety culture criteria are weighted by a combination of Fuzzy Decision Trail and Evaluation Laboratory and Fuzzy ANP methods. Next, different job positions in high-rise projects are ranked using the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution method. Findings demonstrated that the project manager, site superintendent and supervisor occupations had the highest and labourers had the lowest level of safety culture in the high-rise construction industry. Furthermore, factors such as safety supervision and training must be considered more seriously in order to create a positive safety culture among workers.

Selecting Demolition Waste Materials Disposal Alternatives Using Fuzzy TOPSIS Technique

This article describes how in developing countries, millions of tons of construction and demolition wastes (CDWs) are lost every year due to lack of knowledge of recycling significance and/or procedures. Despite the high value of CDWs, high percentage of this waste is either dumped illegally or disposed in the landfills. Disposal methods should consider saving natural resources and maintaining the environmental conditions through maximizing the value of CDWs. This article aims at choosing the most sustainable disposal alternative using Multi-Criteria Decision Making (MCDM) Process, considering several sustainability measure indicators. The research introduces a list containing the most relevant and significant sustainable indicators that affect the selection of alternative for disposal of CDWs. Then, fuzzy TOPSIS technique is applied considering the significant indicators on each alternative to rank and choose the best alternative for disposal of CDWs.

An analysis of barriers for plastic recycling in the Indian plastic industry

Purpose

The purpose of this paper is to develop a new model in which the interrelationship between the barriers can be determined that hinder the implementation of effective recycling processes in the plastic sectors of India.

Design/methodology/approach

Today manufacturers do not want their input to be deemed waste and subsequently be discarded, so their efforts and resources have been channeled into the development of efficient recycling methods. However, there are several barriers hindering the implementation of effective and efficient recycling. In this paper several of the most influential barriers are taken into consideration and implemented in the interpretive structural modeling.

Findings

The results divided the barriers into four clusters and identified the weak and strong barriers and implemented relationships between them.

Research limitations/implications

Globally plastic waste has been steadily increasing. Recycling plastic has received much attention because many companies are using it as a strategic tool to serve their customers and to generate good revenue, but there is a lack of effective recycling units in India. The work of this paper and its results will be helpful in the implementation of an effective and efficient recycling unit for the plastic sector.

Practical implications

The recycling process can be improved by avoiding barriers of PLASTIC recycling.

Originality/value

In this paper, the plastic industries of India are studied and analyzed, and the barriers are found.