Using multi-objective genetic algorithm for partner selection in green supply chain problems
Expert Systems with ApplicationsPublished 28 September 2010
Wei‐Chang Yeh, Mei-Chi Chuang
Citations423
SJR quartileQ1
SJR score1.85
SNIP2.55
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TL;DR
The aim of this research was to develop an optimum mathematical planning model for green partner selection, which involved four objectives such as cost, time, product quality and green appraisal score and adopted two multi-objective genetic algorithms to find the set of Pareto-optimal solutions.
Abstract
Partner selection is an important issue in the supply chain management. Since environment protection has been of concern to public in recent years, and the traditional supplier selection did not consider about this factor; therefore, this paper introduced green criteria into the framework of supplier selection criteria. The aim of this research was to develop an optimum mathematical planning model for green partner selection, which involved four objectives such as cost, time, product quality and green appraisal score. In order to solve these conflicting objectives, we adopted two multi-objective genetic algorithms to find the set of Pareto-optimal solutions, which utilized the weighted sum approach that can generate more number of solutions. In experimental analysis, we introduced a {4, 4, 4, 4} supply chain network structure, and compared average number Pareto-optimal solutions and CPU times of two algorithms.
Keywords
Business, Management and Accounting
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