| dc.description.abstract | In this paper, we look into one of the problems that one often encounters in the order picking of distribution centers. This problem is known as order-batching problem. In an order-batching problem, one has to select two or more orders, batch them, and pick their requested items at the same order-picking trip. Order-batching problem is an important problem in distribution centers that often have to handle many different orders in one day. This is because one can reduce the total travel distance if orders with similar picking locations are batched and picked together. And, the order-picking cost can be reduced as a result. The proposed order-batching method has three major steps to form an order batch. At the first step, similar coefficient of orders between each other will be produced from the order pool. At the second step, Use of different similar coefficients to do fuzzy c-means clustering in order to do so after picking batch of orders. In order batch method also divided into two modes of doing, were known as the ＂single group＂ and ＂multi-groups,＂ and after to compare their advantages and disadvantages. Finally, loading Picking on the car, also used the three batches of ways to carry. For this problem, we propose five different similar coefficients rules, We also propose two different modes for the order batch problem. Furthermore, we also propose three loading methods to order-picking for an order batch. Test problems are then generated and solved by each one of them. Their solution results are collected and compared to see which similar coefficients rule, which order batch mode, which loading method, and what combination of them can result in the best performance in minimizing the total travel distance. It is hoped that the knowledge learned from this study can provide substantial benefits to practitioners in distribution centers. | en_US |