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Multi-Directional Local Search for Sustainable Supply Chain Network Design
Archive ouverte : Article de revue
Edité par HAL CCSD ; Taylor & Francis
International audience. In this paper, we propose a bi-objective MILP formulation to minimize logistics costs as well as CO 2 emissions in a supply chain network design problem with multiple layers of facilities, technology levels and transportation mode decisions. The proposed model aims at investigating the trade-off between cost and CO 2 emissions through supply chain activities (i.e., raw material supply, manufacturing, warehousing, and transportation). To this end, a multi-directional local search (MDLS) metaheuristic is developed. The proposed method provides a limited set of non-dominated solutions ranging from a purely cost effective solution to a purely environmentally effective one. Each iteration of the MDLS consists in performing local searches from all non-dominated solutions. To do so, a Large Neighborhood Search (LNS) algorihtm is used. Extensive experiments based on randomly generated instances of various sizes and features are described. Three classic performance measures are used to compare the set of non-dominated solutions obtained by the MDLS algorithm and by directly solving the MILP model with the epsilon-constraint approach. This paper is concluded by managerial insights about the impact of using greener technology on the supply chain * Corresponding author. Olivier Péton, IMT Atlantique,
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