Multi-objective stochastic multi-site supply chain planning under demand uncertainty considering downside risk. (December 2016)

• Record Type: Journal Article
• Authors: Felfel, Houssem; Ayadi, Omar; Masmoudi, Faouzi
• Is Part Of: Computers & industrial engineering. Volume 102(2016)
• Page Start: 268
• Page End: 279
• Publication Date: 2016-12
• Subjects: Multi-site supply chain -- Multi-objective optimization -- Stochastic programming -- Risk management -- Pareto-optimal solutions; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2016.10.025
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: A multi-site supply chain planning problem under demand uncertainty is considered. A multi-objective stochastic model is developed for the considered problem. The proposed solution approach yields to a front of Pareto optimal robust solutions. A fuzzy decision making approach is applied to select the most preferred Pareto solution. Abstract: In this paper, a multi-period, multi-product, multi-site, multi-stage supply chain planning problem under demand uncertainty is considered. The problem is formulated as a two-stage stochastic linear programming model. In order to generate a robust supply chain planning solution, the downside risk is incorporated into the objective functions of the stochastic programming model as a risk measure. So, the proposed multi-objective stochastic model aims to simultaneously minimize the expected total cost, to minimize the lost customer demand level and to minimize the downside risk. The proposed solution approach yields to a front of Pareto optimal robust solutions. A fuzzy decision making approach is applied to select the most preferred solution among the Pareto optimal robust solutions. A numerical example from a real textile and apparel industry is addressed in order to illustrate the robustness of the supply chain network planning solutions and the effectiveness of the solution approach.