Journal of the Korean Operations Research and Management Science Society (한국경영과학회지)

The Korean Operations Research and Management Science Society (한국경영과학회)
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Workload Smoothness in U-Shaped Production Lines Using Genetic Algorithms

유전알고리듬을 이용한 U라인의 작업부하 평활화

  • 김동묵 (동신대학교 산업공학과) ;
  • 김여근 (전남대학교 산업공학과)
  • Published : 1999.09.01
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Abstract

In just-in-time production systems, U-shaped production lines rather than traditional straight lines are often adopted since they have some advantages. The advantages of U-lines over straight lines are that the workstations required can be reduced and the necessary number of workers can be easily adjusted when the demand rates are changed. In this paper, we present a new heuristic based on genetic algorithm to improve the workload smoothness in the U-line. In the proposed algorithm, a new genetic representation is developed which is specific to the problem being solved. To enhance the capability of searching good solutions, genetic operators are designed by using the problem-specific information and heuristics. Extensive experiments are carried out on well-known test-bed problems in the literature to verify the performance of our algorithm. The computational results show that our algorithm is a promising alternative to existing heuristics.

Keywords

References

  1. IE Interfaces v.12 no.1 양면 조립라인 밸런싱을 위한 유전알고리듬 김여근;김용주;김준혁;박재승
  2. 한국경영과학회지 v.23 no.12 U라인 라인밸런싱을 위한 분지한계법 김여근;김재윤;김동묵;송원섭
  3. ORSAJ. Computing v.6 Genetic Algorithms for Combinatorial Optimization: the Assembly Line Balancing Problem Anderson, E. J.;M. C. Ferris
  4. International Journal of Production Research v.31 Balancing Two-sided Assembly Lines: A Case Study Bartholdi, J.J.
  5. Practical Handbook of Genetic Algorithms 1:Applications How to Apply Genetic Algorithms to Constrained Problems Eiben, A. E.;P. E. Raue;Zs. Ruttkay;Chambers, L.(ed.)
  6. Evolutionary Computation v.2 A New Representation and Operators for Genetic Algorithms Applied to Grouping Problems Falkenauer, E.
  7. AIIIE Trans. v.10 no.1 Balancing Single Model Assembly Comments on A Paper by E.M. Dar-EI(Mansoor) Gehrlein, W.V.;J.H. Patterson
  8. Optimization & Machine Learning Genetic Algorithms in Search Goldberg, D. E.
  9. Complex Systems v.3 Messy Genetic Algorithms: Motivation, Analysis, and First Results Goldberg, D. E.;K. Bradley;D. Kayanmoy
  10. Proceedings of the First ASIA-PACIFIC Decision Sciences Institute Conference U-line Line Balancing with Simulated Annealig Hwang, H.;J.U. Sun;T.H. Yoon
  11. Computers and Operations Research v.25 no.2 A Heuristic-Based Genetic Algorithms for Workload Smoothing in Assembly Lines Kim, Y. K.;Y. J. Kim;Y. K. Cho
  12. Computers and Industrial Engineering no.30 Genetic Algorithms for Assembly Line Balancing with Various Objectives Kim, Y. K.;Y. J. Kim;Y. H. Kim
  13. $4^{th}$ ICGA Intelligent Structual Operators for The k-Way Group Partioning Problem Laszewski, V.
  14. Decision Science v.25 Assembly Line balancing Using genetic Algorithms with Heuristic-Generated Initial Populations and Multiple Evaluation Criteria Leu, Y.Y.;L.A. Matheson;L.P. Rees
  15. Genetic Algorithms+Data Structures=Evolutionary Programs ($2^{nd}$ ed.) Michalewicz, Z.
  16. Management Science v.40 The U-line Line Balancing Problem Miltenburg, G.J.;J. Wijngaard
  17. Toyota Production System ($2^{nd}$ Ed.) Monden, Y.
  18. Journal of Industrial Engineering v.16 no.1 A Heuristic Method of Assembly Line Balancing for Assumptions of Constant or Variable Work Element Times Moodie, C.L.;H.H. Young
  19. International Journal of Production Research v.29 Improving The equality of Workload Asignments in Assembly Lines Rachamadugu, R.;B. Talbot
  20. A Heuristic Program for Assembly Line Balancing Tonge, F.M.
  21. Management Science v.44 no.5 Note Optimal Balancing of U-Shaped Assembly Lines Urban, T.L.