Improving the Decision-making of Reverse Logistics Network Design Part I: A MILP Model under Stochastic Environment
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The study of the network design problems related to reverse supply chain and reverse logistics is of great interest for both academicians and practitioners due to its important role for a sustainable society. However, reverse logistics network design is a complex decision-making problem that involves several interactive factors and faces many uncertainties. Thus, in order to improve the reverse logistics network design, this paper proposes a new optimization model under stochastic environment and an improved solution method for network design of a multi-stage multi-product reveres supply chain. The study is presented in a series of two parts. Part I presents the relevant literature and formulates a stochastic mixed integer linear programming (MILP) for improving the decision-making of the reverse logistics network design. Part II improves the solution method for the proposed stochastic programming and illustrates the application through a numerical experimentation.
Embargoed access. Author's post-print on any open access repository after 12 months after publication. Link to publisher's version: https://doi.org/10.1007/978-981-10-5768-7_46