Journal
APPLIED MATHEMATICAL MODELLING
Volume 37, Issue 14-15, Pages 7855-7864Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.apm.2013.05.021
Keywords
Collaborative supply chain; Order distribution; GA; AHP; TOPSIS
Funding
- Hong Kong Polytechnic University, Chongqing Natural Science Foundation (for Distinguished Young Scholars) [CSCT2010BA2003]
- National Natural Science Foundation of China [61174022]
- National High Technology Research and Development Program of China (863 Program) [2013AA013801]
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Supply chain collaboration is prevalent in today's business model, and has been recognized to be one of the important issues in improving competition strength. Order distribution is to determine which order should be allocated to which supplier, it plays a very important role in a collaborative supply chain, because different order distribution infers different benefit under different criteria. However, there is not much research on the order distribution methodology. This paper adopted a framework of a central coordination system, which is equipped with a multi-criteria genetic optimization feature. In the previous multi-criterion optimization genetic algorithm (MCOGA), the analytic hierarchy process (AHP) is deployed to evaluate the fitness values. In this paper, a modified MCOGA is proposed based on the technique for order preference by similarity to ideal solution (TOPSIS). There are two main parts, namely, searching and evaluation, in genetic algorithms. Compared with the MCOGA, the proposed method takes the advantage of less complexity in the evaluation stage. The numerical example of order distribution is used to illustrate the efficiency of the proposed method. (C) 2013 Elsevier Inc. All rights reserved.
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