1 research outputs found
Evolutionary multiobjective optimization of the multi-location transshipment problem
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