A multiobjective evolutionary approach for an integrated location-inventory problem in vendor-managed inventory systems

In this paper, we propose an integrated model to incorporate inventory control decisions - such as economic order quantity, safety stock and inventory replenishment decisions-into typical facility location models, which are used to solve the distribution network design problem. A simultaneous model is developed considering a stochastic demand, modeling also the risk pooling phenomenon to explore how important supply chain parameters affect the cost savings to be realized from collaborative initiatives such as vendor-managed inventory (VMI). Multiobjective decision analysis is adopted to allow use of a performance measurement system that includes cost, customer service levels (fill rates), and flexibility (responsive level). A multiobjective location-inventory model which permits a comprehensive trade-off evaluation for multi-objective optimization is initially presented. More specifically, a multiobjective evolutionary algorithm is developed to determine the optimal facility location portfolio and inventory control parameters in order to reach best compromise of these conflicting criteria. An experimental study using practical data was then illustrated for the possibility of the proposed approach. Computational results have presented promise solutions in solving a practical-size problem with 50 buyers and 15 potential DCs and proved to be an innovative and efficient approach for so called difficult-to-solve problems.