A genetic algorithm approach for items assign to storage locations in a distribution center
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Order picking is one of the costly activities in the operations of a distribution center. In order to reduce the picking cost, the items must be optimally assigned to the storage locations. This study proposes a method to improve the efficiency for picking operations through storage allocation planning. The objective is to minimize the picking distance. The proposed problem is a quadratic assignment problem (QAP) and is difficult to solve in reasonable time for large-sized problem. We obtain the near optimal solution by a genetic algorithm (GA) approach, because it can avoid trapping into local minimum. Computational results report that the GA is superior to the simulated annealing and taboo search method.