Multi-objective exponential distribution optimizer (MOEDO): a novel math-inspired multi-objective algorithm for global optimization and real-world engineering design problems

The exponential distribution optimizer (EDO) represents a heuristic approach, capitalizing on exponential distribution theory to identify global solutions for complex optimization challenges. This study extends the EDO's applicability by introducing its multi-objective version, the multi-objective EDO (MOEDO), enhanced with elite non-dominated sorting and crowding distance mechanisms. An information feedback mechanism (IFM) is integrated into MOEDO, aiming to balance exploration and exploitation, thus improving convergence and mitigating the stagnation in local optima, a notable limitation in traditional approaches. Our research demonstrates MOEDO's superiority over renowned algorithms such as MOMPA, NSGA-II, MOAOA, MOEA/D and MOGNDO. This is evident in 72.58% of test scenarios, utilizing performance metrics like GD, IGD, HV, SP, SD and RT across benchmark test collections (DTLZ, ZDT and various constraint problems) and five real-world engineering design challenges. The Wilcoxon Rank Sum Test (WRST) further confirms MOEDO as a competitive multi-objective optimization algorithm, particularly in scenarios where existing methods struggle with balancing diversity and convergence efficiency. MOEDO's robust performance, even in complex real-world applications, underscores its potential as an innovative solution in the optimization domain. The MOEDO source code is available at: https://github.com/kanak02/MOEDO .

The Effect of Powder and Emulsion Binders on the Tribological Properties of Particulate Filled Glass Fiber Reinforced Polymer Composites

Investigations into polymer composites are mainly focused on properties dependent on glass fiber reinforcement and particulate fillers. In the present study, the effect of the binder was examined. The specimens were produced with two types of epoxy resin, with similar numbers of glass mat layers and similar proportions of quartz powder added. However, one group was fabricated with an emulsion binder in the glass mats and another group with a powder binder. Attention was concentrated on the tribological properties of the as-prepared composites, though their strength was examined as well. The hardness of the Sikafloor matrix was found to be much more sensitive to the applied binder than that of the MC-DUR matrix. No direct correlation between the microhardness and the specific wear rate was observed and increasing the particulate filler proportion did not cause a direct increase of the specific wear rate. In particular, the highest specific wear rate, around 350 J/g, was reached for both matrices with a 1% quartz addition when the emulsion binder was applied, while in the case of the powder binder it was with 6% quartz with the MC-DUR matrix, and there was no quartz addition with the Sikafloor matrix. The highest microhardness, HV_0.5 = 25, in turn, was reached for the mats with the emulsion binder in the Sikafloor matrix with an addition of 10% quartz powder, while the highest friction coefficient was exhibited in the composite with the MC-DUR matrix, when 1% of the quartz powder and the emulsion binder were applied.

Analysis of the Planar Point Identification Accuracy in CMM Measurements

The paper presents the results of the investigations on the direction-dependent accuracy of the point identification during contact probe measurements with a coordinate measuring machine (CMM). Considering the contact point identified by an orthogonal to the surface probe movement, the transformation of coordinates was made in order to calculate the displacement of the measured point. As a result, the positioning accuracy was estimated in three axes. The experiments demonstrated a strong dependence of the displacement on the declination angle. Moreover, it was found that the directional surface texture which provided different roughness in perpendicular directions, had an impact on the positioning accuracy.

Activated Sintering of Cr2O3-Based Composites by Hot Pressing

The paper presents and discusses questions on structure formation during the sintering process of Cr₂O₃-based composites using the hot pressing method, when a chemical reaction between the components takes place. The task was difficult because Cr₂O₃ decomposes when sintered at temperatures above 1300 °C. The proposed novel method allowed for interaction between aluminum and chromia, thus avoiding the decomposition of the latter. Here, ultrafine aluminum powder played the role of the active agent forming a liquid phase and reacting with Cr₂O₃. The appearance of the solid solutions of (Cr,Al)₂O₃ with different stoichiometry of Cr and Al depended on the aluminum content in the initial mixture. The solid solution significantly strengthened boundaries between composite phases, resulting in the composite material of high fracture toughness between 5 and 7 MPa m^½ and bending strength of ca. 500 MPa. The best mechanical properties exhibited the cermet with 22 wt.% of the restored chromium.

A Hybrid Grey Wolf Optimizer for Process Planning Optimization with Precedence Constraints

Process planning optimization is a well-known NP-hard combinatorial problem extensively studied in the scientific community. Its main components include operation sequencing, selection of manufacturing resources and determination of appropriate setup plans. These problems require metaheuristic-based approaches in order to be effectively and efficiently solved. Therefore, to optimize the complex process planning problem, a novel hybrid grey wolf optimizer (HGWO) is proposed. The traditional grey wolf optimizer (GWO) is improved by employing genetic strategies such as selection, crossover and mutation which enhance global search abilities and convergence of the traditional GWO. Precedence relationships among machining operations are taken into account and precedence constraints are modeled using operation precedence graphs and adjacency matrices. Constraint handling heuristic procedure is adopted to move infeasible solutions to a feasible domain. Minimization of the total weighted machining cost of a process plan is adopted as the objective and three experimental studies that consider three different prismatic parts are conducted. Comparative analysis of the obtained cost values, as well as the convergence analysis, are performed and the HGWO approach demonstrated effectiveness and flexibility in finding optimal and near-optimal process plans. On the other side, comparative analysis of computational times and execution times of certain MATLAB functions showed that the HGWO have good time efficiency but limited since it requires more time compared to considered hybrid and traditional algorithms. Potential directions to improving efficiency and performances of the proposed approach are given in conclusions.