Evolutionary clustering search for flowtime minimization in permutation flow shop

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4771 LNCS, Issue , 2007, Pages 69-81

  Filho, Geraldo Ribeiro ^a   Nagano, Marcelo Seido ^b   Lorena, Luiz Antonio Nogueira ^c  

^a NSK Brasil Ltd   (Brazil)

^b UNIVERSITY OF SÃO PAULO   (Brazil)

^c INSTITUTO NACIONAL DE PESQUISAS ESPACIAIS   (Brazil)

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTERING ALGORITHMS; EVOLUTIONARY ALGORITHMS; HEURISTIC ALGORITHMS; OPTIMIZATION; PROBLEM SOLVING;

FLOW TIME; PERMUTATION FLOW SHOP;

RESOURCE ALLOCATION;

EID: 38149111166     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-75514-2_6     Document Type: Conference Paper

References (29)

1. Garey, M.R., Johnson, D.S., Sethi, R.: The Complexity of flowshop and jobshop scheduling. Mathematics of Operations Research 1, 117-129 (1976)
2. Rinnooy Kan, A.H.G.: Machine Scheduling Problems: Classification, Complexity, and Computations. Nijhoff, The Hahue (1976)
3. Ahmadi, R.H., Bagchi, U.: Improved lower bounds for minimizing the sum of completion times of n jobs over m machines. European Journal of Operational Research 44, 331-336 (1990)
4. Rajendran, C., Chaudhuri, D.: An efficient heuristic approach to the scheduling of jobs in a flowshop. European Journal of Operational Research 61, 318-325 (1991)
5. Rajendran, C.: Heuristic algorithm for scheduling in a flowshop to minimise total flowtime. International Journal Production Economics 29, 65-73 (1993)
6. Ho, J.C.: Flowshop sequencing with mean flowtime objective. European Journal of Operational Research 81, 571-578 (1995)
7. Wang, C., Chu, C., Proth, J.M.: Heuristic approaches for n/m/F/ Ci scheduling problems. European Journal of Operational Research 96, 636-644 (1997)
8. Woo, D.S., Yim, H.S.: A heuristic algorithm for mean flowtime objective in flowshop scheduling. Computers and Operations Research 25, 175-182 (1998)
9. i scheduling problem. European Journal of Operational Research 132, 439-452 (2001)
10. Allahverdi, A., Aldowaisan, T.: New heuristics to minimize total completion time in m-machine flowshops. International Journal of Production Economics 77, 71-83 (2002)
11. Framinan, J.M., Leisten, R.: An efficient constructive heuristic for flowtime minimisation in permutation flow shop. OMEGA 31, 311-317 (2003)
12. Framinan, J.M., Leisten, R., Ruiz-Usano, R.: Comparison of heuristics for flowtime minimisation in permutation flowshops. Computer and Operations Research 32, 1237-1254 (2005)
13. Li, X., Wang, Q., Wu, C.: Efficient composite heuristics for total flowtime minimization in permutation flow shops. Omega (2006) doi: 10.1016-j.omega.2006.11.003
14. Nagano, M.S., Moccellin, J.V.: Reducing mean flow time in permutation flow shop. Journal of the Operational Research Society (2007) doi: 10.1057/palgrave.jors.2602395
15. Rajendran, C., Ziegler, H.: Ant-colony algorithms for permutation flowshop scheduling to minimize makespan/total flowtime of jobs. European Journal of Operational Research 155, 426-438 (2004)
16. Tasgetiren, M.F., Liang, Y.C., Sevkli, M., Gencyilmaz, G.: A particle swarm optimization algorithm for makespan and total flowtime minimization in the permutation flowshop sequencing problem. European Journal of Operational Research 177, 1930-1947 (2007)
17. Stutzle, T.: Applying iterated local search to the permutation flowshop problem. Technical Report, AIDA-98-04, Darmstad University of Technology, Computer Science Department, Intelletics Group, Darmstad, Germany (1998)
18. Merkle, D., Middendorf, M.: An ant algorithm with a new pheromone evaluation rule for total tardiness problems. In: Oates, M.J., Lanzi, P.L., Li, Y., Cagnoni, S., Corne, D.W., Fogarty, T.C., Poli, R., Smith, G.D. (eds.) EvoWorkshops 2000. LNCS, vol. 1803, pp. 287-296. Springer, Heidelberg (2000)
19. Taillard, E.: Benchmarks for basic scheduling problems. European Journal of Operational Research 64, 278-285 (1993)
20. Cotta, C., Fernandez, A.J.: Memetic Algorithms in Planning, Scheduling and Timetabling. Evolutionary Schedulling, pp. 1-30. Springer, Heidelberg (2006)
21. Kleeman, M.P., Lamont, G.B.: Scheduling of flow-shop, job-shop, and combined scheduling problems using MOEAs with fixed and variable length chromosomes. Evolutionary Schedulling, pp. 49-100. Springer, Heidelberg (2006)
22. Bean, J.C.: Genetic algorithm and random keys for sequencing and optimization. ORSA Journal on Computing 6, 154-160 (1994)
23. Watson, J.P., Barbulescu, L., Whitley, L.D., Howe, A.E.: Contrasting structured and random permutation flowshop scheduling problems: Search space topology and algorithm performance. ORSA Journal of Computing 14, 98-123 (2002)
24. Oliveira, A.CM., Lorena, L.A.N.: Detecting promising areas by evolutionary clustering search. In: Bazzan, A.L.C., Labidi, S. (eds.) Advances in Artificial Intelligence. LNCS (LNAI), pp. 385-394. Springer, Heidelberg (2004)
25. Oliveira, A.C.M., Lorena, L.A.N.: Hybrid evolutionary algorithms and clustering search. In: Grosan, C., Abraham, A., Ishibuchi, H. (eds.) Hybrid Evolutionary Systems - Studies in Computational Intelligence. SCI Series, vol. 75, pp. 81-102. Springer, Heidelberg (2007)
26. Nawaz, M., Enscore, E.E., Ham, I.: A heuristic algorithm for the m-machine, n-job flow-shop sequencing problem. OMEGA 11, 91-95 (1983)
27. Glover, F.: Tabu search and adaptive memory programing: Advances, applications and challenges. In: Interfaces in Computer Science and Operations Research, pp. 1-75. Kluwer Academic Publishers, Dordrecht (1996)
28. Syswerda, G.: Uniform crossover in genetic algorithms. In: International Conference on Genetic Algorithms (ICGA), Virginia, USA, pp. 2-9 (1989)
29. Cotta, C., Troya, J.M.: Genetic Forma Recombination in Permutation Flowshop Problems. Evolutionary Computation 6, 25-44 (1998)