Designing a closed‐loop supply chain with stochastic product returns: a Genetic Algorithm approach

In the recent past, some scholars and logisticians have begun to explore the possibility of managing product returns in a more systematic manner. However, up to now there are few studies to address the problem of determining the number and location of centralised product return centres where unknown quantities of returned products from retailers or end‐customers are collected for manufacturers' or distributors' repair facilities. In an effort to fill the void in such a line of research, this paper proposes a non‐linear mixed‐integer programming model and a Genetic Algorithm (GA) that can solve the stochastic network design problem in a closed‐loop supply chain.