A Robust Model for 3PLS to Design a Remanufacturing Logistics Network under the Uncertain Environment

The main objective of this paper is to study the remanufacturing logistics network design problem from third party logistics supplier (3PLS)' perspectives under the uncertain environment. In order to mitigate the potential risks we described the uncertainty of the remanufacturing logistics activities during the procedure of constructing the reverse logistics networks for 3PLS' customers. Therefore, we proposed one fuzzy chance constrained programming model by utilizing the triangular fuzzy numbers to evaluate the uncertainty and fuzziness of the collecting demand and transportation cost. Furthermore, a hybrid genetic algorithm combining with the fuzzy set theory, alpha-cut theory and extending principle is founded to solve the fuzzy model. Application of the numerical example demonstrates that the fuzzy model and solution algorithm is the feasibility to design an effective and efficient remanufacturing logistics network for 3PLS under the uncertain conditions.