An adaptive genetic algorithm approach for the mixed-model assembly line sequencing problem

References

• Alpay , S . 2008 . GRASP with path relinking for a multiple objective sequencing problem for a mixed-model assembly line . International Journal of Production Research , DOI: 10.1080/00207540802158291
   Google Scholar
• Boysen , N , Fliedner , M and Scholl , A . 2007 . Sequencing mixed-model assembly lines to minimize part inventory cost . OR Spectrum , 30 ( 3 ) : 611 – 633 .
   Google Scholar
• Boysen , N , Fliedner , M and Scholl , A . 2009 . Level scheduling of mixed-model assembly lines under storage constraints . International Journal of Production Research , 47 ( 10 ) : 2669 – 2684 .
   Web of Science ®Google Scholar
• Chang , P-C , Hsieh , J-C and Wang , C-Y . 2007 . Adaptive multi-objective genetic algorithms for scheduling of drilling operation in printed circuit board industry . Applied Soft Computing Journal , 7 ( 3 ) : 800 – 806 .
   Google Scholar
• Deb , K . 1999 . “ Evolutionary algorithms for multi-criterion optimization in engineering design ” . In Evolutionary algorithms in engineering and computer science: recent advances in genetic algorithms, evolution strategies, evolutionary programming, genetic programming, and industrial applications , Edited by: Miettinen , K . New York : Wiley .
   Google Scholar
• Drexl , A and Kimms , A . 2001 . Sequencing JIT mixed-model assembly lines under station-load and part-usage constraints . Management Science , 47 ( 3 ) : 489 – 491 .
   Web of Science ®Google Scholar
• Drexl , A , Kimms , A and Matthießen , L . 2006 . Algorithms for the car sequencing and the level scheduling problem . Journal of Scheduling , 9 ( 2 ) : 153 – 176 .
   Web of Science ®Google Scholar
• Eiben , AE , Hinterding , R and Michalewicz , Z . 1999 . Parameter control in evolutionary algorithms . IEEE Transactions on Evolutionary Computing , 3 ( 2 ) : 124 – 141 .
   Web of Science ®Google Scholar
• Herrera , F and Lozano , M . 2003 . Fuzzy adaptive genetic algorithms: design, taxonomy, and future directions . Soft Computing , 7 ( 8 ) : 545 – 562 .
   Web of Science ®Google Scholar
• Ho , JKL . 2005 . A proposed approach for reconfiguration of flexible assembly line systems by motion genes . International Journal of Production Research , 43 ( 9 ) : 1729 – 1749 .
   Web of Science ®Google Scholar
• Huang , YP , Chang , YT and Sandnes , FE . 2006 . “ Using fuzzy adaptive genetic algorithm for function optimization ” . In Fuzzy Information Processing Society , 484 – 489 . Proceedings of the Annual Meeting of the North American, NAFIPS .
   Google Scholar
• Hyun , CJ , Kim , YK and Kim , Y . 1998 . A genetic algorithm for multiple objective sequencing problems in mixed model assembly lines . Computers and Operations Research , 25 ( 7–8 ) : 675 – 690 .
   Web of Science ®Google Scholar
• Kim , YK , Hyun , CJ and Kim , Y . 1996 . Sequencing in mixed model assembly lines: A genetic algorithm approach . Computers & Operations Research , 23 ( 12 ) : 1131 – 1145 .
   Web of Science ®Google Scholar
• Kim , YK , Kim , JY and Kim , Y . 2000 . A coevolutionary algorithm for balancing and sequencing in mixed model assembly lines . Applied Intelligence , 13 ( 3 ) : 247 – 258 .
   Web of Science ®Google Scholar
• Kim , YK , Kim , JY 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 .
   Web of Science ®Google Scholar
• Mansouri , SA . 2005 . A multi-objective genetic algorithm for mixed-model sequencing on JIT assembly lines . European Journal of Operational Research , 167 ( 3 ) : 696 – 716 .
   Web of Science ®Google Scholar
• McMullen , PR . 1998 . JIT sequencing for mixed-model assembly lines with setups using Tabu search . Production Planning & Control , 9 ( 5 ) : 504 – 510 .
   Web of Science ®Google Scholar
• McMullen , PR and Frazier , GV . 2000 . A simulated annealing approach to mixed-model sequencing with multiple objectives on a just-in-time line . IIE Transactions , 32 ( 8 ) : 679 – 686 .
   Web of Science ®Google Scholar
• McMullen , PR , Tarasewich , P and Frazier , GV . 2000 . Using genetic algorithms to solve the multi-product JIT sequencing problem with set-ups . International Journal of Production Research , 38 ( 12 ) : 2653 – 2670 .
   Web of Science ®Google Scholar
• McMullen , PR and Tarasewich , P . 2006 . Multi-objective assembly line balancing via a modified ant colony optimization technique . International Journal of Production Research , 44 ( 1 ) : 27 – 42 .
   Web of Science ®Google Scholar
• Miltenburg , J . 2002 . Balancing and scheduling mixed-model U-shaped production lines . The International Journal of Flexible Manufacturing Systems , 14 ( 2 ) : 119 – 151 .
   Google Scholar
• Miltenburg , J and Sinnamon , G . 1989 . Scheduling mixed-model multi-level just-in-time production systems . International Journal of Production Research , 27 ( 9 ) : 1487 – 1509 .
   Web of Science ®Google Scholar
• Monden , Y . 1993 . Toyota production system , 2nd , GA : Industrial Engineering Press .
   Google Scholar
• Ponnambalam , SG , Aravindan , P and Rao , MS . 2003 . Genetic algorithms for sequencing problems in mixed model assembly lines . Computers & Industrial Engineering , 45 ( 4 ) : 669 – 690 .
   Web of Science ®Google Scholar
• Tan , KC , Lee , TH and Khor , EF . 2002 . Evolutionary algorithms for multi-objective optimization: performance assessments and comparisons . Artificial Intelligence Review , 17 ( 4 ) : 253 – 290 .
   Web of Science ®Google Scholar
• Tseng , H-E . 2008 . Hybrid evolutionary multi-objective algorithms for integrating assembly sequence planning and assembly line balancing . International Journal of Production Research , 46 ( 21 ) : 5951 – 5977 .
   Web of Science ®Google Scholar
• Wester , L and Kilbridge , M . 1964 . “ The assembly line model-mix sequencing problem. ” . In Third international conference on operation research 247 – 260 .
   Google Scholar
• Xu , Z and Liang , M . 2006 . Integrated planning for product module selection and assembly line design/reconfiguration . International Journal of Production Research , 44 ( 11 ) : 2091 – 2117 .
   Web of Science ®Google Scholar
• Yano , CA and Rachamadugu , R . 1991 . Sequencing to minimize work overload in assembly lines with product options . Management Science , 37 ( 5 ) : 572 – 586 .
   Web of Science ®Google Scholar
• Yu , J , Yin , Y and Chen , Z . 2006 . Scheduling of an assembly line with a multi-objective genetic algorithm . The International Journal of Advanced Manufacturing Technology , 28 ( 5–6 ) : 551 – 555 .
   Web of Science ®Google Scholar
• Zhao , S , Zhao , J and Jiao , L . 2005 . “ Adaptive genetic algorithm based approach for evolutionary design and multi-objective optimization of logic circuits. ” . In Proceedings of the 2005 NASA/DoD conference of evolution hardware 67 – 72 .
   Google Scholar