Meta-heuristic algorithms for the multi-item transshipment problem

Differential Evolution (DE) and the Particle Swarm Optimization (PSO) are two evolutionary algorithms that confirmed their efficiency in resolving complex problems. In this paper, we intend to adopt these algorithms to resolve a complex inventory management problem, known in the literature by the transshipment problem. This problem concerns network of collaborative retailers selling items and they collaborate by exchanging items between them. The transshipment problem consists in deriving the optimal replenishment quantity, for each retailer, while a transshipment policy is adopted. A huge body of literature works has addressed this problem where several configurations are investigated. A few of them has addressed the multiitem and the multi-location configuration because of its complexity. We focus in this paper on this complex configuration and we resolve it by the PSO and DE algorithms. Secondly, we compare between the performances of these algorithms according to a set of criteria. Thirdly, we analysis the impact of the studiedtransshipment parameters on the inventory system performance measures.

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