DOI QR코드

DOI QR Code

유전알고리즘을 이용한 지역 집중형 및 분산형 다단계 역물류 네트워크 분석

Analysis of regionally centralized and decentralized multistage reverse logistics networks using genetic algorithm

  • 투고 : 2014.05.15
  • 심사 : 2014.07.18
  • 발행 : 2014.08.30

초록

본 연구에서는 지역적으로 집중화된 역물류네트워크(Regionally centralized multistage reverse logistics network: cmRL)와 지역적으로 분산회된 역물류네트워크(Regionally decentralized multistage reverse logistics network: dmRL)를 제안하고 있다. cmRL과 dmRL 각각은 고려되는 영역 전체와 지역적으로 분산된 세부영역에서의 RL 네트워크로 구성된다. 이들은 혼합정수계획법(Mixed integer programming: MIP) 모델로 공식화되며, 유전알고리즘(Genetic algorithm: GA)을 통해 해를 구하게 된다. 사례연구에서는 두 가지 형태의 RL네트워크를 제시하며 다양한 수행도 척도를 사용하여 cmRL과 dmRL의 효율성을 비교분석하였다. 분석결과 cmRL이 dmRL 보다 더 우수한 수행도를 나타내었다.

This paper proposes regionally centralized multistage reverse logistics (cmRL) networks and regionally decentralized multistage reverse logistics (dmRL) networks. cmRL considers whole area of RL network, while dmRL regionally distributed area of RL network. Each type is formulated by the mixed integer programming (MIP) models, which are realized in genetic algorithm (GA) approach. Two types of numerical experiments using RL network are presented and various measures of performance are used for comparing the efficiency of the cmRL and the dmRL. Finally, it is proved that the performance of the cmRL is superior to that of the dmRL.

키워드

참고문헌

  1. H. Min, H. J. Ko and C. S. Ko, "A Genetic Algorithm Approach to Developing the Multi-echelon Reverse Logistics Network for Product Returns," Omega, Vol. 34, pp. 56-69, 2006. https://doi.org/10.1016/j.omega.2004.07.025
  2. S. K. Srivastava, "Network Design for Reverse Logistics," OMEGA, Vol. 36, pp. 535-548, 2008. https://doi.org/10.1016/j.omega.2006.11.012
  3. H. Y. Na and S. H. Lee, "A Location-routing Problem for Logistics Network Integrating Forward and Reverse Flow," IE Interfaces, Vol. 22, No. 2, pp. 153-164, 2009.
  4. Y. G. Lim and B. J. Jung, "A Study of Location-allocation Model in Integrated Logistics Network Considering Reverse Logistics," 2012 Korean Operations and Management Science Society Autumn Conference, pp. 765-772. 2012.
  5. L. Lin, Y. S. Yun, H. J. Kim and Y. Y. Hwang, "Regionally Distributed and Centralized Reverse Logistics Networks: Genetic Algorithm Approach," 2014 the International Industrial Information Systems Conference, pp. 49-53, 2014
  6. Y. S. Yun, "Comparison of Reverse Logistics Networks in Centralized and Decentralized Areas: Genetic Algorithm Approach," will be appeared in Journal of the Korean Society of Supply Chain Management, 2014.
  7. M. Gen, and R. Cheng, "Genetic Algorithms and Engineering Design," John Wiley & Son, 1997.
  8. J. E. Lee, M. Gen and K. G. Rhee, "Network Model and Optimization of Reverse Logistics by Hybrid Genetic Algorithm," Computers and Industrial Engineering, Vol. 56, pp. 951-964, 2009. https://doi.org/10.1016/j.cie.2008.09.021
  9. Y. S. Yun, M. Gen and R. K. Hwang, "Adaptive Genetic Algorithm to Multi-stage Reverse Logistics Network Design for Product Resale," Information: An International Interdisciplinary Journal, Vol. 15, No. 12, pp. 6117-6138, 2012
  10. Y. S. Yun, "Evaluating Reverse Logistics Networks using Genetic Algorithm Approach," Journal of the Korean Society of Supply Chain Management, Vol. 13, No. 1, pp. 1-14, 2013
  11. Z. Michalewicz, Z. "Genetic Algorithms + Data Structures = Evolution Program," Spring- Verlag, 1994.