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has been cited by the following article:

• TITLE: Development and Comparison of Hybrid Genetic Algorithms for Network Design Problem in Closed Loop Supply Chain

  AUTHORS: Muthusamy Aravendan, Ramasamy Panneerselvam

  KEYWORDS: Closed Loop Supply Chain, Genetic Algorithms, HGA, Meta-Heuristics, MINLP, Model, Network Design, Optimization

  JOURNAL NAME: Intelligent Information Management, Vol.7 No.6, November 24, 2015

  ABSTRACT: This paper presents four different hybrid genetic algorithms for network design problem in closed loop supply chain. They are compared using a complete factorial experiment with two factors, viz. problem size and algorithm. Based on the significance of the factor “algorithm”, the best algorithm is identified using Duncan’s multiple range test. Then it is compared with a mathematical model in terms of total cost. It is found that the best hybrid genetic algorithm identified gives results on par with the mathematical model in statistical terms. So, the best algorithm out of four algorithm proposed in this paper is proved to be superior to all other algorithms for all sizes of problems and its performance is equal to that of the mathematical model for small size and medium size problems.