Evolutionary multiobjective optimization of the multi-location transshipment problem

Nabil Belgasmi (1) , Lamjed Ben Said (1) , Khaled Ghédira (1)

1 SOIE - Stratégies d’Optimisation et Informatique intelligentE

We consider a multi-location inventory system where inventory choices at each location are centrally coordinated. Lateral transshipments are allowed as recourse actions within the same echelon in the inventory system to reduce costs and improve service level. However, this transshipment process usually causes undesirable lead times. In this paper, we propose a multiobjective model of the multi-location transshipment problem which addresses optimizing three conflicting objectives: (1) minimizing the aggregate expected cost, (2) maximizing the expected fill rate, and (3) minimizing the expected transshipment lead times. We apply an evolutionary multiobjective optimization approach using the strength Pareto evolutionary algorithm (SPEA2), to approximate the optimal Pareto front. Simulation with a wide choice of model parameters shows the different trades-off between the conflicting objectives.

Mots clés: Multi-location transshipment problem; Multiobjective optimization problems; Multiobjective evolutionary algorithms; Pareto optimality

Domaines: Intelligence artificielle [cs.AI]; Optimisation et contrôle [math.OC]

Nabil Belgasmi, Lamjed Ben Said, Khaled Ghédira. Evolutionary multiobjective optimization of the multi-location transshipment problem. Operational Research, 2008, 8 (2), pp.167-183. ⟨10.1007/s12351-008-0015-5⟩. ⟨hal-00564069⟩