Abstract
In this paper, a multi-objective, multi-period, multi-product stochastic model for a multi-site supply chain planning problem under demand uncertainty is proposed. The decisions to be made include the amounts of product to be produced, the amounts of products to be transported between the different sites and customers as well as the amounts of inventory of finished or semi-finished products. The developed model aims simultaneously to minimize the expected total cost, to maximize the customer demand satisfaction level and to minimize the downside risk. The e-constraint method is applied to solve the considered model and to generate the set of Pareto optimal solutions. This set of Pareto represents the trade-off between the different objective functions. Then, an integrated approach of the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods is applied in order to select the best compromise Pareto solution. A numerical example is presented to illustrate the proposed approach.
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Acknowledgements
We would like to acknowledge the financial support provided by the Mobility of researchers and research for the creation of value (MOBIDOC) as well as LINDO Systems, Inc for giving us a free educational research license of the extended version of LINGO 14.0 software package.
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Felfel, H., Masmoudi, F. (2018). Integrated AHP-TOPSIS Approach for Pareto Optimal Solution Selection in Multi-site Supply Chain Planning. In: Haddar, M., Chaari, F., Benamara, A., Chouchane, M., Karra, C., Aifaoui, N. (eds) Design and Modeling of Mechanical Systems—III. CMSM 2017. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-66697-6_30
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DOI: https://doi.org/10.1007/978-3-319-66697-6_30
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