Multiobjective hybrid genetic algorithm for reverse logistics network design of inventory systems with backordering

Jeong Eun Lee, Kyong Gu Rhee, HeeHyol Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

The reverse logistics is the process flow of used-products that are collected to be reproduced so that they can be sold again to customers after some processing. Within this perspective, we formulated a mathematical model of the reuse system as a reverse logistics with two objectives functions: one is minimizing cost of reverse logistics network problem, (i.e. transportation cost, disposal cost, purchase cost and inventory holding cost) another is just-in-time delivery, and minimizes the costs of backorders and inventories in manufacturer in all periods. This paper proposes a new multiobjective hybrid genetic algorithm approach, and shows how the performance of multiobjective genetic algorithm can be improved by hybridization with Fuzzy Logic Control (FLC). In the experimental results comparing CPLEX, pri-awGA (priority-based adaptive weight Genetic Algorithm) and mo-hGA (multiobjective Hybrid Genetic Algorithm), we demonstrated the effectiveness of mo-hGA such as shortness of computational time and better solutions.

Original languageEnglish
Title of host publicationIEEM2010 - IEEE International Conference on Industrial Engineering and Engineering Management
Pages2318-2322
Number of pages5
DOIs
Publication statusPublished - 2010
EventIEEE International Conference on Industrial Engineering and Engineering Management, IEEM2010 - Macao
Duration: 2010 Dec 72010 Dec 10

Other

OtherIEEE International Conference on Industrial Engineering and Engineering Management, IEEM2010
CityMacao
Period10/12/710/12/10

Fingerprint

Logistics
Genetic algorithms
Costs
Fuzzy logic
Mathematical models
Processing

Keywords

  • Backorder control
  • Inventory
  • Multiobjective hybrid genetic algoriehm (mo-hGA)
  • Reverse logistics

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering

Cite this

Lee, J. E., Rhee, K. G., & Lee, H. (2010). Multiobjective hybrid genetic algorithm for reverse logistics network design of inventory systems with backordering. In IEEM2010 - IEEE International Conference on Industrial Engineering and Engineering Management (pp. 2318-2322). [5674151] https://doi.org/10.1109/IEEM.2010.5674151

Multiobjective hybrid genetic algorithm for reverse logistics network design of inventory systems with backordering. / Lee, Jeong Eun; Rhee, Kyong Gu; Lee, HeeHyol.

IEEM2010 - IEEE International Conference on Industrial Engineering and Engineering Management. 2010. p. 2318-2322 5674151.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Lee, JE, Rhee, KG & Lee, H 2010, Multiobjective hybrid genetic algorithm for reverse logistics network design of inventory systems with backordering. in IEEM2010 - IEEE International Conference on Industrial Engineering and Engineering Management., 5674151, pp. 2318-2322, IEEE International Conference on Industrial Engineering and Engineering Management, IEEM2010, Macao, 10/12/7. https://doi.org/10.1109/IEEM.2010.5674151
Lee JE, Rhee KG, Lee H. Multiobjective hybrid genetic algorithm for reverse logistics network design of inventory systems with backordering. In IEEM2010 - IEEE International Conference on Industrial Engineering and Engineering Management. 2010. p. 2318-2322. 5674151 https://doi.org/10.1109/IEEM.2010.5674151
Lee, Jeong Eun ; Rhee, Kyong Gu ; Lee, HeeHyol. / Multiobjective hybrid genetic algorithm for reverse logistics network design of inventory systems with backordering. IEEM2010 - IEEE International Conference on Industrial Engineering and Engineering Management. 2010. pp. 2318-2322
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