Simultaneous solving of balancing and sequencing problems in mixed-model assembly line systems

References

• Al-Aomar , R . 2006 . Incorporating robustness into genetic algorithm search of stochastic simulation outputs . Simulation Modelling Practice and Theory , 14 ( 3 ) : 201 – 223 .
   Web of Science ®Google Scholar
• Bäck , T . 1996 . Evolutionary algorithms in theory and practice , 1st ed , New York : Oxford University Press .
   Google Scholar
• 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 .
   Web of Science ®Google Scholar
• Beyer , HG and Schwefel , HP . 2002 . Evolution strategies – a comprehensive introduction . Natural Computing , 1 ( 1 ) : 3 – 52 .
   Google Scholar
• Bock , S , Rosenberg , O and Brackel , TV . 2006 . Controlling mixed-model assembly lines in real-time by using distributed systems . European Journal of Operational Research , 168 ( 3 ) : 880 – 904 .
   Web of Science ®Google Scholar
• Boysen , N , Fliedner , M and Scholl , A . 2007 . A classification of assembly line balancing problems . European Journal of Operational Research , 183 ( 2 ) : 674 – 693 .
   Web of Science ®Google Scholar
• Boysen , N , Fliedner , M and Scholl , A . 2009 . Sequencing mixed-model assembly lines: survey, classification and model critique . European Journal of Operational Research , 192 ( 2 ) : 349 – 373 .
   Web of Science ®Google Scholar
• Bukchin , Y and Rabinowitch , I . 2006 . A branch-and-bound based solution approach for the mixed-model assembly line-balancing problem for minimizing stations and task duplication costs . European Journal of Operational Research , 174 ( 1 ) : 492 – 508 .
   Web of Science ®Google Scholar
• Bukchin , J , Dar-El , EM and Rubinovitz , J . 2002 . Mixed model assembly line design in a make-to-order environment . Computers & Industrial Engineering , 41 ( 4 ) : 405 – 421 .
   Web of Science ®Google Scholar
• Cevikcan , E , Durmusoglu , MB and Unal , ME . 2009 . A team-oriented design methodology for mixed model assembly systems . Computers & Industrial Engineering , 56 ( 2 ) : 576 – 599 .
   Web of Science ®Google Scholar
• Cochran , WG and Cox , GM . 1992 . Experimental designs , 2nd ed , New York : Wiley .
   Google Scholar
• Costa , L and Oliveira , P . 2001 . Evolutionary algorithms approach to the solution of mixed integer non-linear programming problems . Computers & Chemical Engineering , 25 ( 2–3 ) : 257 – 266 .
   Web of Science ®Google Scholar
• Dar-El , EM and Nadivi , A . 1981 . A mixed–model sequencing application . International Journal of Production Research , 19 ( 1 ) : 69 – 84 .
   Web of Science ®Google Scholar
• Erel , E , Gocgun , Y and Sabuncuoğlu , İ . 2007 . Mixed-model assembly line sequencing using beam search . International Journal of Production Research , 45 ( 22 ) : 5265 – 5284 .
   Web of Science ®Google Scholar
• Esmaeilian , GR . 2009 . Allocating and balancing of mixed model production through the parallel assembly lines . European Journal of Scientific Research , 31 ( 4 ) : 616 – 631 .
   Google Scholar
• Gutjahr , AL and Nemhauser , GL . 1964 . An algorithm for the line balancing problem . Management Science , 11 ( 2 ) : 308 – 315 .
   Web of Science ®Google Scholar
• Hicks , CR . 1993 . Fundamental concepts in the design of experiments , 4th ed , New York : Oxford University Press .
   Google Scholar
• Hwang , R and Katayama , H . 2010 . Integrated procedure of balancing and sequencing for mixed-model assembly lines: a multiobjective evolutionary approach . International Journal of Production Research , 48 ( 21 ) : 6417 – 6441 .
   Web of Science ®Google Scholar
• Hyun , CJ , Kim , Y and Kim , YK . 1998 . A genetic algorithm for multiple objective sequencing problems in mixed model assembly lines . Computers & Operations Research , 25 ( 7–8 ) : 675 – 690 .
   Web of Science ®Google Scholar
• Karabati , S and Sayin , S . 2003 . Assembly line balancing in a mixed-model sequencing environment with synchronous transfers . European Journal of Operational Research , 149 ( 2 ) : 417 – 429 .
   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
• Miltenburg , J . 2002 . Balancing and scheduling mixed-model u-shaped production lines . International Journal of Flexible Manufacturing Systems , 14 ( 2 ) : 119 – 151 .
   Google Scholar
• Montgomery , DC . 2000 . Design and analysis of experiments , 5th ed , New York : Wiley .
   Google Scholar
• Naderi , B , Zandieh , M and Fatemi Ghomi , SMT . 2009 . Scheduling job shop problems with sequence-dependent setup times . International Journal of Production Research , 47 ( 21 ) : 5959 – 5976 .
   Web of Science ®Google Scholar
• Özcan , U and Toklu , B . 2009 . Multiple-criteria decision-making in two-sided assembly line balancing: a goal programming and a fuzzy goal programming models . Computers & Operations Research , 36 ( 6 ) : 1955 – 1965 .
   Web of Science ®Google Scholar
• Rekiek , B and Delchambre , A . 2006 . Assembly line design: the balancing of mixed-model hybrid assembly lines with genetic algorithms , 1st ed , London : Springer .
   Google Scholar
• Roberts , SD and Villa , CD . 1970 . On a multiproduct assembly line-balancing problem . AIIE Transactions , 2 ( 4 ) : 361 – 364 .
   Google Scholar
• Sabuncuoglu , I , Gocgun , Y and Erel , E . 2008 . Backtracking and exchange of information: methods to enhance a beam search algorithm for assembly line scheduling . European Journal of Operational Research , 186 ( 3 ) : 915 – 930 .
   Web of Science ®Google Scholar
• Sarker , BR and Pan , H . 1998 . Designing a mixed-model assembly line to minimize the costs of idle and utility times . Computers & Industrial Engineering , 34 ( 3 ) : 609 – 628 .
   Web of Science ®Google Scholar
• Sawik , T . 2002 . Monolithic vs. hierarchical balancing and scheduling of a flexible assembly line . European Journal of Operational Research , 143 ( 1 ) : 115 – 124 .
   Web of Science ®Google Scholar
• Scholl , A . 2010. Homepage for assembly line optimization research. Available from: <http://www.assembly–line–balancing.de/> [Accessed 10 July 2010]
   Google Scholar
• Simaria , AS and Vilarinho , PM . 2004 . A genetic algorithm based approach to the mixed-model assembly line balancing problem of type ii . Computers & Industrial Engineering , 47 ( 4 ) : 391 – 407 .
   Web of Science ®Google Scholar
• Taguchi , G . 1986 . Introduction to quality engineering: designing quality into products and processes , 1st ed , White Plains, NY : Asian Productivity Organization .
   Google Scholar
• Tavakkoli-Moghaddam , R and Rahimi-Vahed , AR . 2006 . Multi-criteria sequencing problem for a mixed-model assembly line in a JIT production system . Applied Mathematics and Computation , 181 ( 2 ) : 1471 – 1481 .
   Web of Science ®Google Scholar
• Thomopoulos , NT . 1967 . Line balancing-sequencing for mixed-model assembly . Management Science , 14 ( 2 ) : 59 – 75 .
   Google Scholar
• Tsai , LH . 1995 . Mixed-model sequencing to minimize utility work and the risk of conveyor stoppage . Management Science , 41 ( 3 ) : 485 – 495 .
   Web of Science ®Google Scholar
• Whitley , D . 2001 . An overview of evolutionary algorithms: practical issues and common pitfalls . Information and Software Technology , 43 ( 14 ) : 817 – 831 .
   Web of Science ®Google Scholar