A Multi-Stage Stochastic Mixed-Integer Linear Programming to Design an Integrated Production-Distribution Network under Stochastic Demands - Derakhshi, Mohammad; Niaki, Seyed Taghi Akhavan; Niaki, Seyed Armin Akhavan (Industrial Engineering & Management Systems, 2018)
Supply chain management has gained much interest from researchers and practitioners in recent years. Proposingpractical models that efficiently address different aspects of the supply chain is a difficult challenge. This researchinvestigates an integrated production-distribution supply chain problem. The developed model incorporates partieswith a specified number of processes to obtain raw materials from the suppliers in order to convert them to semi andfinal products. These products are then distributed through warehouses to end-distributors having uncertain demands. This uncertainty is captured as a dynamic stochastic data process during the planning horizon and is modeled into amulti-stage stochastic mixed integer linear program using a scenario tree approach. For large-size instances, a hybridexact-approximate algorithm is proposed, where its effectiveness is assessed via several numerical cases. Furthermore,the model is generalized to its bi-objective version by considering the accessibility of the products based on the safetystock policy of the companies involved. In the end, an existing algorithm is combined with the ε-constraint method toobtain an approximate Pareto front. KCI Citation Count: 0