期刊
EXPERT SYSTEMS WITH APPLICATIONS
卷 41, 期 7, 页码 3569-3575出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2013.11.004
关键词
Distribution strategy; Open vehicle routing problem; Uncertainty; Robust optimization; Differential evolution algorithm
类别
资金
- National Natural Science Foundation of China [71001035, 70925006]
- Program for New Century Excellent Talents in University [NCET-13-0181]
We investigate the open vehicle routing problem with uncertain demands, where the vehicles do not necessarily return to their original locations after delivering goods to customers. We firstly describe the customer's demand as specific bounded uncertainty sets with expected demand value and nominal value, and propose the robust optimization model that aim at minimizing transportation costs and unsatisfied demands in the specific bounded uncertainty sets. We propose four robust strategies to cope with the uncertain demand and an improved differential evolution algorithm (IDE) to solve the robust optimization model. Then we analyze the performance of four different robust strategies by considering the extra costs and unmet demand. Finally, the computational experiments indicate that the robust optimization greatly avoid unmet demand while incurring a small extra cost and the optimal return strategy is the best strategy by balancing the trade-off the cost and unmet demand among different robust strategies. Crown Copyright (C) 2013 Published by Elsevier Ltd. All rights reserved.
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