Browse > Article

A Symbiotic Evolutionary Algorithm for Balancing and Sequencing Mixed Model Assembly Lines with Multiple Objectives  

Kim, Yeo-Keun (전남대학교 공과대학 산업공학과)
Lee, Sang-Seon (전남대학교 공과대학 산업공학과)
Publication Information
Journal of the Korean Operations Research and Management Science Society / v.35, no.3, 2010 , pp. 25-43 More about this Journal
Abstract
We consider a multi-objective balancing and sequencing problem in mixed model assembly lines, which is important for an efficient use of the assembly lines. In this paper, we present a neighborhood symbiotic evolutionary algorithm to simultaneously solve the two problems of balancing and model sequencing under multiple objectives. We aim to find a set of well-distributed solutions close to the true Pareto optimal solutions for decision makers. The proposed algorithm has a two-leveled structure. At Level 1, two populations are operated : One consists of individuals each of which represents a partial solution to the balancing problem and the other consists of individuals for the sequencing problem. Level 2, which is an upper level, works one population whose individuals represent the combined entire solutions to the two problems. The process of Level 1 imitates a neighborhood symbiotic evolution and that of Level 2 simulates an endosymbiotic evolution together with an elitist strategy to promote the capability of solution search. The performance of the proposed algorithm is compared with those of the existing algorithms in convergence, diversity and computation time of nondominated solutions. The experimental results show that the proposed algorithm is superior to the compared algorithms in all the three performance measures.
Keywords
Mixed Model Assembly Lines; Balancing and Sequencing Problem; Multiobjective Evolutionary Algorithm; Symbiotic Evolutionary Algorithm; Pareto Optimal Solutions;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 Veldhuizen, D.A.V. and G.B., Lamont, "Multiobjective Evolutionary Algorithms：Analyzing the State-of-the-art," Evolutionary Computation, Vol.8, No.2(2000), pp.125-147.   DOI   ScienceOn
2 Zitzler, E. and L. Thiele, "Mutlobjective Evolutionary Algorithms：A Comparative Case Study and the Strength Pareto Approach," IEEE Transactions on Evolutionary Computation, Vol.3, No.4(1999), pp.257-271.   DOI   ScienceOn
3 Zitzler, E., "Evolutionary Algorithms for Multiobjective Optimization：Methods and Applications," Dissertation, Swiss Federal Institute of Technology(ETH) Zurich, 1999.
4 Zitzler, E., M. Laumanns, and L. Thiele, "SPEA2：Improving the Strength Pareto Evolutionary Algorithm," Technical Report 103, Computer Engineering and Networks Laboratory( TIK), Swiss Federal Institute of Technology( ETH) Zurich, Gloriastrasse 35, CH-8092 Zurich, Switzerland, 2001.
5 Potter, M.A., "The Design and Analysis of a Computational Model of Cooperative Coevolution," Ph.D. dissertation, George Mason University, 1997.
6 Schaffer, J.D., "Multiple Objective Optimization with Vector Evaluated Genetic Algorithms," In Genetic Algorithms and their Applications： Proceedings of the First International Conference on Genetic Algorithms, Lawrence Erlbaum, (1985), pp.93-100.
7 Srinivas, N. and K. Deb, "Multiobjective Optimization Using Nondominated Sorting in Genetic Algorithms," Evolutionary Computation, Vol.2(1985), pp.221-248.
8 Tan, K.C., T.H. LEE, and E.F. Khor, "Evolutionary Algorithms for Multi-Objective Optimization：Performance Assessments and Comparison," Artificial Intelligence Review, Vol.17(2002), pp.253-290.
9 Thomopoulos, N.T., "Mixed Model Line Balancing with Smoothed Station Assignment," Management Science, Vol.16(1970), pp.593- 603.   DOI   ScienceOn
10 Thomopoulos, N.T., "Line Balancing-Sequencing for Mixed-Model Assembly," Management Science, Vol.14(1967), pp.59-75.   DOI
11 Kim, Y.K., J.Y. Kim, and Y. Kim, "A Coevolutionary Algorithm for Balancing and Sequencing in mixed model assembly lines," Applied Intelligence, Vol.13(2000), pp.247-258.   DOI   ScienceOn
12 Knowles, J.D. and D.W. Corne, "The Pareto Archived Evolution Strategy：A New Baseline Algorithm for Multi-Objective Optimization," Proceedings of the First IEEE International Conference on Evolutionary Computation, (1999), pp.98-105.
13 Macaskill, J.C., "Production-line Balances for Mixed-Model Lines," Management Science, Vol.19(1972), pp.423-434.   DOI   ScienceOn
14 Margulis, L., Symbiosis in Cell Evolution, W. H. Freeman, San Francisco, 1981.
15 Miltenburg, J., "Level Schedules for Mixed- Model Assembly Lines in Just-In-Time Production Systems," Management Science, Vol. 35(1989), pp.192-207.   DOI   ScienceOn
16 Horn, J., N. Nafpliotis, and D.E. Goldberg, "A Niched Pareto Genetic Algorithm for Multiobjective Optimization," Proceedings of the First IEEE international Conference on Evolutionary Computation, Vol.1(1994), pp.82-87.
17 Okamura, K. and H. Yamashina, "A Heuristic Algorithm for the Assembly Line Model-Mix Sequencing Problem to Minimize the Risk of Stopping the Conveyor," International Journal of production Research, Vol.17(1979), pp. 233-247.   DOI   ScienceOn
18 Deb, K., Multi-Objective Optimization Using Evolutionary Algorithm, John Wiley and Sons Ltd, Chichester, England, 2001.
19 Goldberg, D.E., Genetic Algorithms in Search, Optimization, and Machine Learning, Addison Wesley, Reading, Massachusetts, 1989.
20 Kim, J.Y., Y. Kim, and Y.K. Kim, "An Endosymbiotic Evolutionary Algorithm for Optimization," Applied Intelligence, Vol.15(2001), pp.117-130.   DOI   ScienceOn
21 Coello, C.A.C., G.B. Lamont, and D.A.V. Veldhhuizen, Evolutionary Algorithms for Solving Multi-Objective Problems, Springer, New York, 2007.
22 Kim, Y.K., C.J. Hyun, and Y. Kim, "Sequencing in Mixed Model Assembly Lines：a Genetic Algorithm Approach," Computers and Operations Research, Vol.23(1996), pp.1131-1145.   DOI   ScienceOn
23 Bard, J.F., E.M. Dar-El, and A. Shtub, "An Analytic Framework for Sequencing Mixed Model Assembly Lines," International Journal of Production Research, Vol.30(1992), pp.35-48.   DOI   ScienceOn
24 Burns, L.D. and C.F. Daganzo, "Assembly Lines Job Sequencing Principles," International Journal of Production Research, Vol.25(1987), pp.71-99.   DOI   ScienceOn
25 Dar-El, E.M. and A. Navidi, "A Mixed-model Sequencing Application," International Journal of Production Research, Vol.19(1981), pp.69-84.   DOI
26 김여근, 이수연, 김용주, "혼합모델조립라인에서 작업부하의 평활화를 위한 유전알고리듬", 대한산업공학회지, 제23권, 제3호(1996), pp.515-532.
27 Davidor, Y., "A Naturally occurring niche and species phenomenon：The Model and First Results," Proceedings of the 4th International Conference on Genetic Algorithms, San Mateo, CA, (1991), pp.257-263.
28 Deb, K., S. Agrawal, A. Pratap, and T. Meyarivan, "A Fast Elitist Non-Dominated Sorting Genetic Algorithm for Multi-Objective Optimization：NSGA-II," In M.S. et al.(Ed.), Parallel Problem Solving from Nature-PPSN VI, Berlin, Springer, (2000), pp.849-858.
29 김여근, 윤복식, 이상복, 메타휴리스틱, 영지문화사, 1997.
30 신경석, 김여근, "다목적 최적화를 위한 공생 진화알고리즘", 한국경영과학회지, 제32권, 제1호 (2007), pp.77-91.   과학기술학회마을
31 Arcus, A.L., "An analysis of a Computer Method of Sequencing Assembly Line Operations," Ph.D. dissertation, University of California, 1963.