期刊
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
卷 74, 期 -, 页码 59-69出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.omega.2017.01.006
关键词
Application; Bin packing; Two-dimensional vector packing; General costs; Memetic algorithm
资金
- National Natural Science Foundation of China [71501092, 71571094, 71401065, 71501075]
- NRF Singapore [R266000105281/R266E00105281/R266000105282]
- MOE-AcRF-Tier 1 [R266000096133, R266000096731, R266000100646]
- Natural Science Foundation of Jiangxi Province [20151BAB217006]
The two-dimensional vector packing problem with general costs (2DVPP-GC) arises in logistics where shipping items of different weight and volume are packed into cartons before being transported by a courier company. In practice, the delivery cost of a carton of items is usually retrieved from a cost table. The costs may not preserve any known mathematical function since it could specify arbitrary price at any possible weight. Such a general pricing scheme meets a majority of real-world bin packing applications, where the price of delivery service is determined by many complicated and correlated factors. Compared to the classical bin packing problem and its variants, the 2DVPP-GC is more complex and challenging. To solve the 2DVPP-GC with minimizing the total cost, we propose a memetic algorithm to compute solutions of high quality. Fitness functions and improved operators are proposed to achieve effectiveness. Computational experiments on a variety of test instances show that the algorithm is competent to solve the 2DVPP-GC. In particular, optimal solutions are found in a second for all the test instances that have a known optimal solution. (C) 2017 Elsevier Ltd. All rights reserved.
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