A hybrid multiobjective evolutionary approach for flexible job-shop scheduling problems

Mathematical Problems in Engineering

Volumn 2012, Issue , 2012, Pages

  Xiong, Jian ^a   Xu, Tan ^b   Yang, Ke Wei ^a   Xing, Li Ning ^a   Chen, Ying Wu ^a  

^a NATIONAL UNIVERSITY OF DEFENSE TECHNOLOGY   (China)

^b SHENZHEN INSTITUTE OF INFORMATION TECHNOLOGY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

CRITICAL PATHS; CROWDING DISTANCE; EVOLUTIONARY APPROACH; FLEXIBLE JOB-SHOP SCHEDULING PROBLEM; GENETIC OPERATORS; LOCAL SEARCH; MINIMIZING MAKESPAN; MULTI OBJECTIVE; PARETO OPTIMAL SOLUTIONS;

SCHEDULING ALGORITHMS;

PROBLEM SOLVING;

EID: 84866133152     PISSN: 1024123X     EISSN: 15635147     Source Type: Journal    
DOI: 10.1155/2012/478981     Document Type: Article

References (47)

1. Garey M. R., Johnson D. S., Sethi R., The complexity of flowshop and job shop scheduling. Mathematics of Operations Research 1976 1 2 117 129 2-s2.0-0016952078
2. Jain A. S., Meeran S., Deterministic job-shop scheduling: past, present and future. European Journal of Operational Research 1999 113 2 390 434 2-s2.0-0033102020
3. Brucker P., Schlie R., Job-shop scheduling with multi-purpose machines. Computing 1990 45 4 369 375 2-s2.0-0025531716 10.1007/BF02238804
4. Kacem I., Hammadi S., Borne P., Approach by localization and multiobjective evolutionary optimization for flexible job-shop scheduling problems. IEEE Transactions on Systems, Man and Cybernetics Part C 2002 32 1 1 13 2-s2.0-0036464279 10.1109/TSMCC.2002.1009117 (Pubitemid 34789920)
5. Kacem I., Hammadi S., Borne P., Pareto-optimality approach for flexible job-shop scheduling problems: hybridization of evolutionary algorithms and fuzzy logic. Mathematics and Computers in Simulation 2002 60 35 245 276 2-s2.0-0037201140 10.1016/S0378-4754(02)00019-8
6. Xia W., Wu Z., An effective hybrid optimization approach for multi-objective flexible job-shop scheduling problems. Computers and Industrial Engineering 2005 48 2 409 425 2-s2.0-14044268702 10.1016/j.cie.2005.01.018 (Pubitemid 40274933)
7. Hsu T., Dupas R., Jolly D., Goncalves G., Evaluation of mutation heuristics for the solving of multiobjective flexible job shop by an evolutionary algorithm. Proceedings of the IEEE International Conference on Systems, Man and Cybernetics October 2002 655 660 2-s2.0-0038407278
8. Zhang G., Shao X., Li P., Gao L., An effective hybrid particle swarm optimization algorithm for multi-objective flexible job-shop scheduling problem. Computers and Industrial Engineering 2009 56 4 1309 1318 2-s2.0-67349174559 10.1016/j.cie.2008.07.021
9. Liu H., Abraham A., Wang Z., A multi-swarm approach to multi-objective flexible job-shop scheduling problems. Fundamenta Informaticae 2009 95 4 465 489 2-s2.0-77049113541 10.3233/FI-2009-160
10. Gao J., Gen M., Sun L., Zhao X., A hybrid of genetic algorithm and bottleneck shifting for multiobjective flexible job shop scheduling problems. Computers and Industrial Engineering 2007 53 1 149 162 2-s2.0-34447289102 10.1016/j.cie.2007.04.010 (Pubitemid 47042310)
11. Gao J., Sun L., Gen M., A hybrid genetic and variable neighborhood descent algorithm for flexible job shop scheduling problems. Computers and Operations Research 2008 35 9 2892 2907 2-s2.0-38749142590 10.1016/j.cor.2007. 01.001 (Pubitemid 351186807)
12. Xing L. N., Chen Y. W., Yang K. W., Multi-objective flexible job shop schedule: design and evaluation by simulation modeling. Applied Soft Computing Journal 2009 9 1 362 376 2-s2.0-53749102032 10.1016/j.asoc.2008.04.013
13. Xing L. N., Chen Y. W., Yang K. W., An efficient search method for multi-objective flexible job shop scheduling problems. Journal of Intelligent Manufacturing 2009 20 3 283 293 2-s2.0-67349126259 10.1007/s10845-008-0216-z
14. Li J. Q., Pan Q. K., Liang Y. C., An effective hybrid tabu search algorithm for multi-objective flexible job-shop scheduling problems. Computers and Industrial Engineering 2010 59 4 647 662 2-s2.0-78049356373 10.1016/j.cie.2010.07.014
15. Bagheri A., Zandieh M., Mahdavi I., Yazdani M., An artificial immune algorithm for the flexible job-shop scheduling problem. Future Generation Computer Systems 2010 26 4 533 541 2-s2.0-75049086134 10.1016/j.future.2009.10. 004
16. Vilcot G., Billaut J.-C., A tabu search algorithm for solving a multicriteria flexible job shop scheduling problem. International Journal of Production Research 2011 49 23 6963 6980 2-s2.0-84855798863 10.1080/00207543. 2010.526016
17. Ho N. B., Tay J. C., Solving multiple-objective flexible job shop problems by evolution and local search. IEEE Transactions on Systems, Man and Cybernetics Part C 2008 38 5 674 685 2-s2.0-50649083283 10.1109/TSMCC.2008. 923888
18. Frutos M., Olivera A. C., Tohmé F., A memetic algorithm based on a NSGAII scheme for the flexible job-shop scheduling problem. Annals of Operations Research 2010 181 1 745 765 2-s2.0-78649788124 10.1007/s10479-010- 0751-9
19. Deb K., Pratap A., Agarwal S., Meyarivan T., A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation 2002 6 2 182 197 2-s2.0-0036530772 10.1109/4235.996017 (Pubitemid 34555372)
20. Wang X., Gao L., Zhang C., Shao X., A multi-objective genetic algorithm based on immune and entropy principle for flexible job-shop scheduling problem. International Journal of Advanced Manufacturing Technology 2010 51 58 757 767 2-s2.0-78650179774 10.1007/s00170-010-2642-2
21. Li J. Q., Pan Q. K., Gao K. Z., Pareto-based discrete artificial bee colony algorithm for multi-objective flexible job shop scheduling problems. International Journal of Advanced Manufacturing Technology 2011 55 912 1159 1169 2-s2.0-79961021676 10.1007/s00170-010-3140-2
22. Li J.-Q., Pan Q.-K., Chen J., A hybrid Pareto-based local search algorithm for multi-objective flexible job shop scheduling problems. International Journal of Production Research 2012 50 4 1063 1078 2-s2.0-84860470398 10.1080/00207543.2011.555427
23. Moslehi G., Mahnam M., A Pareto approach to multi-objective flexible job-shop scheduling problem using particle swarm optimization and local search. International Journal of Production Economics 2011 129 1 14 22 2-s2.0-78649330971 10.1016/j.ijpe.2010.08.004
24. Balas E., Machine sequencing via disjunctive graphs: an implicit enumeration algorithm. Operations Research 1969 17 941 957
25. Deb K., Tiwari S., Omni-optimizer: a generic evolutionary algorithm for single and multi-objective optimization. European Journal of Operational Research 2008 185 3 1062 1087 2-s2.0-34848886877 10.1016/j.ejor.2006.06.042 (Pubitemid 47498807)
26. Ulrich T., Bader J., Zitzler E., Integrating decision space diversity into hypervolume-based multiobjective search. Proceedings of the 12th Annual Genetic and Evolutionary Computation Conference (GECCO '10) July 2010 Portland, Ore, USA 455 462 2-s2.0-77955857300 10.1145/1830483.1830569
27. Ishibuchi H., Akedo N., Nojima Y., A many-objective test problem for visually examining diversity maintenance behavior in a decision space. Proceedings of the 13th Annual Genetic and Evolutionary Computation Conference (GECCO '11) 2011 649 656 2-s2.0-84860405107 10.1145/2001576.2001666
28. Gen M., Tsujimura Y., Kubota E., Solving job-shop scheduling problems by genetic algorithm. Proceedings of the 16th International Conference on Computer and Industrial Engineering October 1994 Ashikaga, Japan 1577 1582 2-s2.0-0028756620
29. Pezzella F., Morganti G., Ciaschetti G., A genetic algorithm for the Flexible Job-shop Scheduling Problem. Computers and Operations Research 2008 35 10 3202 3212 2-s2.0-40249118429 10.1016/j.cor.2007.02.014 (Pubitemid 351335142)
30. Hartmann S., Kolisch R., Experimental evaluation of state-of-the-art heuristics for the resource-constrained project scheduling problem. European Journal of Operational Research 2000 127 2 394 407 2-s2.0-0034559432 10.1016/S0377-2217(99)00485-3
31. Kolisch R., Hartmann S., Experimental investigation of heuristics for resource-constrained project scheduling: an update. European Journal of Operational Research 2006 174 1 23 37 2-s2.0-33845270624 10.1016/j.ejor.2005.01. 065 (Pubitemid 44866841)
32. Murata T., Ishibuchi H., Tanaka H., Genetic algorithms for flowshop scheduling problems. Computers and Industrial Engineering 1996 30 4 1061 1071 2-s2.0-0030241443 10.1016/0360-8352(96)00053-8 (Pubitemid 126375914)
33. Murata T., Ishibuchi H., Tanaka H., Multi-objective genetic algorithm and its applications to flowshop scheduling. Computers and Industrial Engineering 1996 30 4 957 968 2-s2.0-0030241820 10.1016/0360-8352(96)00045-9 (Pubitemid 126375906)
34. Xiong J., Chen Y.-W., Yang K.-W., Zhao Q.-S., Xing L.-N., A hybrid multiobjective genetic algorithm for robust resource-constrained project scheduling with stochastic durations. Mathematical Problems in Engineering 2012 2012 24 786923 2-s2.0-84859765834 10.1155/2012/786923
35. Hartmann S., A competitive genetic algorithm for resource-constrained project scheduling. Naval Research Logistics 1998 45 7 733 750 2-s2.0-0032188522 (Pubitemid 128587349)
36. Shadrokh S., Kianfar F., A genetic algorithm for resource investment project scheduling problem, tardiness permitted with penalty. European Journal of Operational Research 2007 181 1 86 101 2-s2.0-33847297058 10.1016/j.ejor.2006.03.056
37. Moscato P., Cheng R., A memetic approach for the traveling salesman problem: implementation of a computational ecology for combinatorial optimization on message-passing systems. Proceedings of the International Conference on Parallel Computing and Transputer Applications 1992 Amsterdam, The Netherlands
38. Ishibuchi H., Murata T., Multi-objective genetic local search algorithm. Proceedings of the IEEE International Conference on Evolutionary Computation (ICEC '96) May 1996 119 124 2-s2.0-0029701517
39. Ishibuchi H., Murata T., A multi-objective genetic local search algorithm and its application to flowshop scheduling. IEEE Transactions on Systems, Man and Cybernetics Part C 1998 28 3 392 403 2-s2.0-0032141635 (Pubitemid 128748638)
40. Zhang C., Li P., Guan Z., Rao Y., A tabu search algorithm with a new neighborhood structure for the job shop scheduling problem. Computers and Operations Research 2007 34 11 3229 3242 2-s2.0-34047181443 10.1016/j.cor.2005. 12.002 (Pubitemid 46517853)
41. Ishibuchi H., Yoshida T., Murata T., Balance between genetic search and local search in memetic algorithms for multiobjective permutation flowshop scheduling. IEEE Transactions on Evolutionary Computation 2003 7 2 204 223 2-s2.0-0038273913 10.1109/TEVC.2003.810752
42. Lin J.-Y., Chen Y.-P., Analysis on the collaboration between global search and local search in memetic computation. IEEE Transactions on Evolutionary Computation 2011 15 5 608 623 6031912 2-s2.0-80054693896 10.1109/TEVC.2011.2150754
43. Ishibuchi H., Hitotsuyanagi Y., Wakamatsu Y., Nojima Y., How to choose solutions for local search in multiobjective combinatorial memetic algorithms. Proceedings of the 11th International Conference on Parallel Problem Solving from Nature (PPSN '10) 2010
44. Karimi N., Zandieh M., Karamooz H. R., Bi-objective group scheduling in hybrid flexible flowshop: a multi-phase approach. Expert Systems with Applications 2010 37 6 4024 4032 2-s2.0-77549083772 10.1016/j.eswa.2009.09.005
45. Rahmati S. H. A., Zandieh M., Yazdani M., Developing two multi-objective evolutionary algorithms for the multi-objective flexible job shop scheduling problem. International Journal of Advanced Manufacturing Technology. In press 2-s2.0-84858596898 10.1007/s00170-012-4051-1
46. Brandimarte P., Routing and scheduling in a flexible job shop by tabu search. Annals of Operations Research 1993 41 3 157 183 2-s2.0-34250084648 10.1007/BF02023073
47. Li J., Pan Q., Xie S., An effective shuffled frog-leaping algorithm for multi-objective flexible job shop scheduling problems. Applied Mathematics and Computation 2012 218 18 9353 9371 2-s2.0-84860437097 10.1016/j.amc.2012.03.018