Applying meta-heuristic algorithms for an integrated production-distribution problem in a two level supply chain

Bank, M.; Mazdeh, M.; Heydari, M.

Abstract: Supply Chain Management (SCM) is the set of approaches used for the appropriate integration and utilization of suppliers, manufacturers, warehouses and retailers to ensure the production and delivery of products to end users in the right quantities and at the right time. Integration of the stages in the supply chain can make it more effective and profitable as a whole. In the present study, an integrated production and distribution problem in a two-stage supply chain is considered. The supply chain consists of m manufacturers with different locations and rates of production, and a distributer that delivers the ordered products to customers in different locations. Here, products are seasonal and perishable and must be delivered before a specified time. To characterize the problem, a Mixed Integer Programming (MIP) model is proposed and to solve the proposed model, a Hybrid Simulated Annealing (HSA) and a Genetic Algorithm (GA) with mixed repair and penalize strategies are introduced. Computational results of HSA are compared with those of the GA algorithm as the current best algorithm for solving similar problems in the literature.

How to cite this paper

        APA: Bank, M., Mazdeh, M & Heydari, M. (2020). Applying meta-heuristic algorithms for an integrated production-distribution problem in a two level supply chain. Uncertain Supply Chain Management, 8(1), 77-92.
    

        Chicago/Turabian: Bank, M., Mazdeh, M & Heydari, M. 2020. "Applying meta-heuristic algorithms for an integrated production-distribution problem in a two level supply chain." Uncertain Supply Chain Management 8, no. 1 (2020): 77-92.
    

        AMA: Bank, M., Mazdeh, M & Heydari, M. Applying meta-heuristic algorithms for an integrated production-distribution problem in a two level supply chain. Uncertain Supply Chain Management. 2020;8(1):77-92.
    

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