LAUSR

Abstract We present a metaheuristic for planning the distribution of items in closed-loop supply chains. This metaheuristic composes sequences of transfer and repair actions to generate plans iteratively. It uses a local search algorithm based on an efficient data structure to construct and select improving sequences at each step. An experimental comparison with a mixed integer programming approach shows its scalability and robustness on a variety of instances. We also study and discuss the ability to support different distribution policies.