A modified colonial competitive algorithm for the mixed-model U-line balancing and sequencing problem

International Journal of Production Research

Volumn 50, Issue 18, 2012, Pages 5117-5131

  Lian, Kunlei ^a   Zhang, Chaoyong ^a   Gao, Liang ^a   Shao, Xinyu ^a  

^a HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

Colonial competitive algorithm; Genetic algorithm; Mixed model U line balancing and sequencing

Indexed keywords

CO-EVOLUTIONARY ALGORITHM; COLONIAL COMPETITIVE ALGORITHMS; COMPUTATIONAL RESULTS; ENDOSYMBIOTIC EVOLUTIONARY ALGORITHMS; ILLUSTRATIVE EXAMPLES; LINE BALANCING; MARKET DEMAND; MIXED-MODEL U-LINE; MODEL SEQUENCING; NP-HARD; SEQUENCING PROBLEMS; U-SHAPED ASSEMBLY LINES;

GENETIC ALGORITHMS; SIMULATED ANNEALING;

PROBLEM SOLVING;

EID: 84867034634     PISSN: 00207543     EISSN: 1366588X     Source Type: Journal    
DOI: 10.1080/00207543.2011.653453     Document Type: Article

References (26)

1. Atashpaz-Gargari, E., Hashemzadeh, F., and Lucas, C., 2008. Designing mimo piid controller using colonial competitive algorithm: Applied to distillation column process. In: IEEE World Congress on Computational Intelligence, 1-6 June, Hong Kong. Piscataway, NJ: IEEE, 1929-1934.
2. Atashpaz-Gargari, E. and Lucas, C., 2007. Imperialist competitive algorithm: An algorithm for optimization inspired by imperialistic competitioned. IEEE Congress on Evolutionary Computation, 7, 4661-4666.
3. Bagher, M., Zandieh, M., and Farsijani, H., 2011. Balancing of stochastic u-type assembly lines: An imperialist competitive algorithm. The International Journal of Advanced Manufacturing Technology, 54 (1-4), 271-285.
4. Becker, C. and Scholl, A., 2006. A survey on problems and methods in generalized assembly line balancing. European Journal of Operational Research, 168 (3), 694-715.
5. Erel, E. and Sarin, S.C., 1998. A survey of the assembly line balancing procedures. Production Planning & Control, 9 (5), 414-434.
6. Ghosh, S. and Gagnon, R.J., 1989. A comprehensive literature review and analysis of the design, balancing and scheduling of assembly systems. International Journal of Production Research, 27 (4), 637.
7. Hwang, R. and Katayama, H., 2009. A multi-decision genetic approach for workload balancing of mixed-model u-shaped assembly line systems. International Journal of Production Research, 47 (14), 3797-3822.
8. Kara, Y., 2008. Line balancing and model sequencing to reduce work overload in mixed-model u-line production environments. Engineering Optimization, 40 (7), 669-684.
9. Kara, Y., Ozcan, U., and Peker, A., 2007a. An approach for balancing and sequencing mixed-model JIT u-lines. International Journal of Advanced Manufacturing Technology, 32 (11/12), 1218-1231.
10. Kara, Y., Ozcan, U., and Peker, A., 2007b. Balancing and sequencing mixed-model just-in-time u-lines with multiple objectives. Applied Mathematics and Computation, 184 (2), 566-588.
11. Kara, Y. and Tekin, M., 2009. A mixed integer linear programming formulation for optimal balancing of mixed-model u-lines. International Journal of Production Research, 47 (15), 4201-4233.
12. Karimi, N., Zandieh, M., and Najafi, A.A., 2011. Group scheduling in flexible flow shops: A hybridised approach of imperialist competitive algorithm and electromagnetic-like mechanism. International Journal of Production Research, 49 (16), 4965-4977.
13. Kim, Y.K., Kim, J.Y., and Kim, Y., 2000a. A coevolutionary algorithm for balancing and sequencing in mixed model assembly lines. Applied Intelligence, 13 (3), 247-258.
14. Kim, Y.K., Kim, J.Y., and Kim, Y., 2006. An endosymbiotic evolutionary algorithm for the integration of balancing and sequencing in mixed-model u-lines. European Journal of Operational Research, 168 (3), 838-852.
15. Kim, Y.K., Kim, S.J., and Kim, J.Y., 2000b. Balancing and sequencing mixed-model u-lines with a co-evolutionary algorithm. Production Planning & Control: The Management of Operations, 11 (8), 754-764.
16. Miltenburg, J., 2002. Balancing and scheduling mixed-model u-shaped production lines. International Journal of Flexible Manufacturing Systems, 14 (2), 123-155.
17. Nazari-Shirkouhi, S., et al., 2010. Solving the integrated product mix-outsourcing problem using the imperialist competitive algorithm. Expert Systems with Applications, 37 (12), 7615-7626.
18. Niknam, T., et al., 2011. An efficient hybrid algorithm based on modified imperialist competitive algorithm and k-means for data clustering. Engineering Applications of Artificial Intelligence, 24 (2), 306-317.
19. Özcan, U., Kellegöz, T., and Toklu, B., 2011. A genetic algorithm for the stochastic mixed-model u-line balancing and sequencing problem. International Journal of Production Research, 49 (6), 1605-1626.
20. Rajabioun, R., Atashpaz-Gargari, E., and Lucas, C., 2008. Colonial competitive algorithm as a tool for nash equilibrium point achievement. In: O. Gervasi, B. Murgante, A. Laganá, D. Taniar, Y. Mun, and M.L. Gavrilova, eds. Computational science and its applications - iccsa 2008. Berlin: Springer, 680-695.
21. Sarayloo, F. and Tavakkoli-Moghaddam, R., 2010. Imperialistic competitive algorithm for solving a dynamic cell formation problem with production planning. In: D.-S. Huang, X. Zhang, C.A. Reyes Garcia, and L. Zhang, eds. Advanced intelligent computing theories and applications. Berlin: Springer, 266-276.
22. Scholl, A. and Becker, C., 2006. State-of-the-art exact and heuristic solution procedures for simple assembly line balancing. European Journal of Operational Research, 168 (3), 666-693.
23. Scholl, A. and Klein, R., 1999. Ulino: Optimally balancing u-shaped JIT assembly lines. International Journal of Production Research, 37 (4), 721-736.
24. Shokrollahpour, E., Zandieh, M., and Dorri, B., 2010. A novel imperialist competitive algorithm for bi-criteria scheduling of the assembly flowshop problem. International Journal of Production Research, 49 (11), 3087-3103.
25. Sparling, D. and Miltenburg, J., 1998. The mixed-model u-line balancing problem. International Journal of Production Research, 36 (2), 485-501.
26. Tseng, H.E., 2006. Guided genetic algorithms for solving a larger constraint assembly problem. International Journal of Production Research, 44 (3), 601-625.