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 methods for the proposed stochastic programming and illustrates the application through a numerical experimentation.
CITATION STYLE
Yu, H., & Solvang, W. D. (2018). Improving the Decision-Making of Reverse Logistics Network Design Part II: An Improved Scenario-Based Solution Method and Numerical Experimentation. In Lecture Notes in Electrical Engineering (Vol. 451, pp. 421–429). Springer Verlag. https://doi.org/10.1007/978-981-10-5768-7_45
Mendeley helps you to discover research relevant for your work.