A hybrid algorithm for stochastic single-source capacitated facility location problem with service level requirements

Salemi, H.

Abstract: Facility location models are observed in many diverse areas such as communication networks, transportation, and distribution systems planning. They play significant role in supply chain and operations management and are one of the main well-known topics in strategic agenda of contemporary manufacturing and service companies accompanied by long-lasting effects. We define a new approach for solving stochastic single source capacitated facility location problem (SSSCFLP). Customers with stochastic demand are assigned to set of capacitated facilities that are selected to serve them. It is demonstrated that problem can be transformed to deterministic Single Source Capacitated Facility Location Problem (SSCFLP) for Poisson demand distribution. A hybrid algorithm which combines Lagrangian heuristic with adjusted mixture of Ant colony and Genetic optimization is proposed to find lower and upper bounds for this problem. Computational results of various instances with distinct properties indicate that proposed solving approach is efficient.

How to cite this paper

        APA: Salemi, H. (2016). A hybrid algorithm for stochastic single-source capacitated facility location problem with service level requirements. International Journal of Industrial Engineering Computations, 7(2), 295-308.
    

        Chicago/Turabian: Salemi, H. 2016. "A hybrid algorithm for stochastic single-source capacitated facility location problem with service level requirements." International Journal of Industrial Engineering Computations 7, no. 2 (2016): 295-308.
    

        AMA: Salemi, H. A hybrid algorithm for stochastic single-source capacitated facility location problem with service level requirements. International Journal of Industrial Engineering Computations. 2016;7(2):295-308.
    

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