169
Views
22
CrossRef citations to date
0
Altmetric
Original Articles

A new multiobjective genetic algorithm with heterogeneous population for solving flowshop scheduling problems

&
Pages 465-477 | Published online: 16 Jul 2007

References

  • Arroyo , J. E.C. and Armentano , V. A. 2005 . Genetic local search for multi-objective flowshop scheduling problems . Eur. J. Opl Res. , 167 : 717 – 738 .
  • Bagchi , T. P. 1999 . Multiobjective Scheduling by Genetic Algorithms , Dordrecht, , The Netherlands : Kluwer Academic Publishers .
  • Bagchi , T. P. 2001 . “ Pareto-optimal solutions for multi-objective production scheduling problems ” . In Evolutionary Multi-Criterion Optimization , Edited by: Zitzler , E. , Deb , K. , Thiele , L. , Coelo , C. A. C. and Corne , D. 458 – 471 . New York : Springer Verlag .
  • Brizuela , C. , Sannomiya , N. and Zhao , Y. 2001 . “ Multi-objective flow-shop: Preliminary Results ” . In Evolutionary Multi-Criterion Optimization , Edited by: Zitzler , E. , Deb , K. , Thiele , L. , Coello , C. A. C. and Corne , D. 443 – 457 . New York : Springer Verlag .
  • Chang , P. -C. , Hsieh , J. -C. and Lin , S. G. 2002 . The development of gradual priority weighting approach for the multiobjective flowshop scheduling problem . Int. J. Prod. Econ. , 79 : 171 – 183 .
  • Coello , C. A.C. , van Veldhuizen , D. A. and Lamont , G. B. 2002 . Evolutionary Algorithms for Solving Multi-Objective Problems , Dordrecht, , The Netherlands : Kluwer Academic Press .
  • Cochran , J. K. , Horng , S. and Fowler , J. W. 2003 . A multi-population genetic algorithm to solve multi-objective scheduling problems for parallel machines . Comput. Op. Res. , 30 : 1087 – 1102 .
  • Deb , K. 2001 . Multi-objective Optimization using Evolutionary Algorithms , New York : John Wiley .
  • Deb , K. , Pratap , A. , Agarwal , S. and Meyarivan , T. 2002 . A fast and elitist multi-objective genetic algorithm: NSGA-II . IEEE Trans Evolutionary Comput. , 6 : 182 – 197 .
  • Fonseca , C. M. and Fleming , P. J. 1995 . An overview of evolutionary algorithms in multi-objective optimization . Evolutionary Comput. J. , 3 : 1 – 16 .
  • Framinen , J. M. , Leisten , R. and Ruiz-Usano , R. 2002 . Efficient heuristics for flowshop sequencing with the objectives of makespan and flowtime minimization . Eur. J. Opl Res. , 141 : 559 – 569 .
  • Garen , J. 2004 . “ A genetic algorithm for tackling multiobjective job-shop scheduling problems ” . In Metaheuristics for Multiobjective Optimisation , Edited by: Gandilbleux , X. , Servaux , M. , Sorensen , K. and T'kindt , V. 201 – 219 . New York : Springer .
  • Gen , M. and Cheng , R. 1997 . Genetic Algorithms and Engineering Design , New York : John Wiley .
  • Goldberg , D. E. 1989 . Genetic Algorithms in Search, Optimization and Machine Learning , New York : Addison Wesley .
  • Goldberg , D. and Lingle , R. 1985 . Allele, loci and the traveling salesman problem . Proceedings of the First International Conference on Genetic Algorithms . 1985 .
  • Horn , J. , Nafploitis , N. and Goldberg , D. 1994 . A niched Pareto genetic algorithm for multi-objective optimization . Proceedings of the First IEEE Conference on Evolutionary Computation . 1994 . pp. 82 – 87 .
  • Ishibuchi , H. and Murata , T. 1998 . A multi-objective genetic local search algorithm and its application to flow-shop scheduling . IEEE Trans Systems, Man and Cybernetics – Part C: Applic. Rev. , 28 : 392 – 403 .
  • Jaskiewicz , A. 1998 . “ Genetic local search for multiple objective combinatorial optimization ” . In Technical Report RA-GL4/98 , Poland : Institute of Computing Science, Poznan University of Technology .
  • Kusiak , A. 1990 . Intelligent Manufacturing System , Englewood Cliffs, NJ : Prentice Hall .
  • Michalewicz , Z. 1994 . Genetic Algorithms + Data Structure = Evolution Programs , 2nd edition , New York : Springer-Verlag .
  • Murata , T. , Ishibuchi , H. and Tanaka , H. 1996 . Multi-objective genetic algorithm and its application to flowshop scheduling . Comput. Ind. Eng. , 130 : 957 – 968 .
  • Pinedo , M. 1995 . Scheduling: Theory, Algorithms and Systems , Englewood Cliffs, NJ : Prentice-Hall .
  • Rajendran , C. and Ziegler , H. 2004 . Ant colony algorithms for permutation flowshop scheduling to minimize makespan/total flowtime of jobs . Eur. J. Opl Res. , 155 : 426 – 438 .
  • Ruiz , R. , Maroto , C. and Alcaraz , J. in press . Two new robust genetic algorithms for the flowshop scheduling problem . Omega: The International Journal of Management Science ,
  • Scaffer , J. D. 1985 . Multiple objective optimization with vector evaluated genetic algorithms . Proceedings of the First International Conference on Genetic Algorithms . 1985 . pp. 93 – 100 . Lawrence Erlbaum Associates .
  • Silva , J. D.L. , Burke , E. K. and Petrovic , S. 2004 . “ An introduction to multiobjective metaheuristics for scheduling and timetabling ” . In Metaheuristics for Multiobjective Optimisation , Edited by: GAndibleux , X. , Sevaux , M. , Sorensen , K. and T'kindt , V. 91 – 129 . New York : Springer Verlag .
  • Srinivas , N. and Deb , K. 1994 . Multi-objective function optimization using non-dominated sorting genetic algorithms . Evolutionary Comput. J. , 2 : 221 – 248 .
  • Taillard , E. 1993 . Benchmarks for basic scheduling problems . Eur. J. Opl Res. , 64 : 278 – 285 .
  • Talbi , E. , Rahoual , M. , Mabed , M. H. and Dhaenens , C. 2001 . “ A hybrid evolutionary approach for multicriteria optimization problems: application to flow shop ” . In Evolutionary Multi-Criterion Optimization , Edited by: Zitzler , E. , Deb , K. , Thiele , L. , Coello , C. A.C. and Corne , D. 416 – 428 . New York : Springer Verlag .
  • Tamura , H. , Shibata , T. and Hatono , I. 1999 . “ Multiobjective combinatorial optimization for performance evaluation by a meta-heuristic satisficing tradeoff method ” . In Global Production Management , Edited by: Mertins , K. , Krause , O. and Schallock , B. 490 – 497 . Dordrecht, , The Netherlands : Kluwer Academic Publisher .
  • Varadharajan , T. K. and Rajendran , C. 2005 . A multi-objective simulated-annealing algorithm for scheduling in flowshops to minimize the makespan and total flowtime of jobs . Eur. J. Opl Res. , 167 : 772 – 795 .

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.