Multi-objective evolutionary approach for solving facility layout problem using local search

Proceedings of the ACM Symposium on Applied Computing

Volumn , Issue , 2010, Pages 1155-1156

  Ripon, Kazi Shah Nawaz ^a   Glette, Kyrre ^a   Høvin, Mats ^a   Tørresen, Jim ^a  

^a UNIVERSITY OF OSLO   (Norway)

Author keywords

jumping gene genetic algorithm (JGGA); pareto optimality

Indexed keywords

COMBINATORIAL OPTIMIZATION PROBLEMS; EVOLUTIONARY APPROACH; FACILITY LAYOUT PROBLEMS; JUMPING GENE; JUMPING GENE GENETIC ALGORITHM (JGGA); LAYOUT SOLUTIONS; LOCAL SEARCH; MANUFACTURING INDUSTRIES; MULTI OBJECTIVE; MULTIPLE CRITERIA; NONDOMINATED SOLUTIONS; PARETO-OPTIMALITY; SIMULATION RESULT; SINGLE OBJECTIVE;

COMBINATORIAL OPTIMIZATION; COMPUTATIONAL COMPLEXITY; GENETIC ALGORITHMS; MULTIOBJECTIVE OPTIMIZATION; PARETO PRINCIPLE; PLANT LAYOUT;

CONVERGENCE OF NUMERICAL METHODS;

EID: 77954751925     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1774088.1774333     Document Type: Conference Paper

References (5)

1. Ripon, K.S.N., Glette, K., Mirmotahari, O., Høvin. M., and Tørresen, J. Pareto optimal based evolutionary approach for solving multi-objective facility layout problem. In Proceedings of the 16th International Conference on Neural Information Processing, (Bangkok, Thailand, December 1-5, 2009), 2009, (accepted).
2. Singh, S.P., and Singh, V.K. An improved heuristic approach for multi-objective facility layout problem. Int J Prod Res., iFirst, (2009), 1-24.
3. Ye, M., and Zhou, G. A local genetic approach to multi-objective facility layout problems with fixed aisles. Int J Prod Res, 45, 22 (2007), 5243-5264. (Pubitemid 47537050)
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5. Schott, J. R. Fault Tolerant Design Using Single and Multa-Crateria Genehc Algorathm, Master's Thesis, Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Boston, MA, 1995.