A Decision-Making Framework for Inventory Positioning in an Omnichannel Business Environment

Omnichannel is an evolving business model that has been gaining increased popularity among retailers. This business model allows firms to use a variety of channels to interact with their customers and fulfill their orders. Customers can order online and pick up later in the store, or they can choose to have the products delivered from a nearby store. Due to the complexity of fulfilling customer orders via omnichannel models, positioning inventory is a key challenge in supporting this type of business model. This article presents a framework for assisting companies in deciding under what condition to centralize or decentralize their inventory to fulfill customer orders without disrupting the shopping experience.

Selection of Transportation Channels in Closed-Loop Supply Chain Using Meta-Heuristic Algorithm

This article presents a closed-loop supply chain (CLSC) network design problem consisting of both forward and reverse material flows. Here, a four-echelon single-product system is introduced in which multiple transportation channels are considered between the nodes of each echelon. Each design is analyzed for the optimum cost, time and environmental impact which form objective functions. The problem is modeled as a tri-objective mixed integer linear programming (MILP) model. The cost objective aggregates the opening cost (fixed cost) and the variable costs in both forward and reverses material flow. The time objective considers the longest transportation time from plants to customers and reverse. Factors of environmental impact are categorized and weighed using an analytic network process (ANP) which forms the environmental objective function. A genetic algorithm (GA) has been applied as a solution methodology to solve the MILP model. Ultimately, a case problem is also used to illustrate the model developed and concluding remarks are made regarding the results.

A Just-in-Time Inventory Model with Preventive Maintenance and Defect Rate

In competitive market environments, businesses employ Just-In-Time (JIT) systems not only to reduce costs, but also to enhance their business partnerships. Although product quality level is essential for maintaining competitiveness, traditional inventory models do not consider defect rate, which is the main determinant of product quality. Also, in real working environments, machines break down after long operating times, which increases product defect rate. Therefore, an effective preventive maintenance policy is needed to ensure that machinery is reliable. Reworking defective items is another important inventory problem. To answer the above questions regarding varying defect rate, preventive maintenance and rework, this study developed an integrated two-echelon inventory model to determine the best production quantity, delivery frequency and preventive maintenance schedule under JIT production and delivery policy. The model results can be used to minimize total cost.