Optimization of integrated supply chain network problem using hybrid genetic algorithm approach

  • Abstract
  • Keywords
  • References
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  • Abstract

    In this paper, an integrated supply chain network (ISCN) problem is designed. The ISCN problem is composed of forward and reverse logistics and represented by a nonlinear mixed integer programming (NMIP). The objective of the ISCN problem is to maximize the total profit which is consisted of total revenues and total costs resulting from its implementation. A hybrid genetic algorithm (HGA) approach proposed in this paper is applied to solve the NMIP. In numerical experiment, five scales of the ISCN problem are presented and they are solved using the proposed HGA approach and some conventional approaches. Experimental results show that the proposed HGA approach outperforms the others.

  • Keywords

    Integrated supply chain network problem, hybrid genetic algorithm, forward logistics, reverse logistics, nonlinear mixed integer programming.

  • References

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Article ID: 8905
DOI: 10.14419/ijet.v7i1.1.8905

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