An evolutionary approach for multi-objective optimization of the integrated location-inventory distribution network problem in vendor-managed inventory

被引:66
|
作者
Liao, Shu-Hsien [1 ]
Hsieh, Chia-Lin [2 ]
Lai, Peng-Jen [3 ]
机构
[1] Tamkang Univ, Dept Management Sci & Decis Making, Taipei, Taipei County, Taiwan
[2] Aletheia Univ, Dept Ind Management & Enterprise Informat, Taipei, Taiwan
[3] Natl Kaohsiung Normal Univ, Dept Math, Kaohsiung, Taiwan
关键词
Integrated location-inventory distribution network system; Vendor-managed inventory (VMI); Supply chain management; Multi-objective optimization; Genetic algorithm; MODEL;
D O I
10.1016/j.eswa.2010.12.072
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Vendor-managed inventory (VMI) is one of the emerging solutions for improving the supply chain efficiency. It gives the supplier the responsibility to monitor and decide the inventory replenishments of their customers. In this paper, an integrated location-inventory distribution network problem which integrates the effects of facility location, distribution, and inventory issues is formulated under the VMI setup. We presented a Multi-Objective Location-Inventory Problem (MOLIP) model and investigated the possibility of a multi-objective evolutionary algorithm based on the Non-dominated Sorting Genetic Algorithm (NSGA2) for solving MOLIP. To assess the performance of our approach, we conduct computational experiments with certain criteria. The potential of the proposed approach is demonstrated by comparing to a well-known multi-objective evolutionary algorithm. Computational results have presented promise solutions for different sizes of problems and proved to be an innovative and efficient approach for many difficult-to-solve problems. (C) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码:6768 / 6776
页数:9
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