Supply chain planning with integrated decision making in resource allocation

Abstract

This study develops a mixed integer nonlinear programming (MINLP) model to plan supply chains by dealing with resource allocation. The model considers resource allocation decisions at both the strategic and tactic levels, and involves three supply chain stages: supply, production, and distribution and their interactions. This formulation is motivated by the importance of simultaneously dealing with decisions at two levels and systematically addressing the three stages. The model deals with multicommodity, instead of a single product, supply chain planning to meet diverse customer requirements. Along with the classical constraints considered in the literature, constraints related to product structures, facility pairwise relationships, and supplier priority are identified and formulated. To solve such a highly constrained, large scale MINLP model, we develop an approach based on genetic algorithm (GA). An illustrative example not only demonstrates the proposed MINLP model for planning supply chains but also shows the advantage of GA-based solving approach.