An effective PSO-based memetic algorithm for flow shop scheduling

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

Volumn 37, Issue 1, 2007, Pages 18-27

  Liu, Bo ^a   Wang, Ling ^a   Jin, Yi Hui ^a  

^a TSINGHUA UNIVERSITY   (China)

Author keywords

Adaptive meta Lamarckian learning; Memetic algorithm (MA); Particle swarm optimization (PSO); Permutation flow shop scheduling

Indexed keywords

COMPUTATIONAL COMPLEXITY; COMPUTER SIMULATION; CONVERGENCE OF NUMERICAL METHODS; OPTIMIZATION; POLYNOMIALS; PROBABILITY; RANDOM PROCESSES;

ADAPTIVE META-LAMARCKIAN LEARNING; MEMETIC ALGORITHM (MA); PARTICLE SWARM OPTIMIZATION (PSO); PERMUTATION FLOW SHOP SCHEDULING;

SCHEDULING ALGORITHMS;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; BIOMIMETICS; COMPUTER PROGRAM; COMPUTER SIMULATION; INDUSTRY; METHODOLOGY; ORGANIZATION AND MANAGEMENT; SYSTEMS THEORY; THEORETICAL MODEL; WORKPLACE;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BIOMIMETICS; COMPUTER SIMULATION; INDUSTRY; MODELS, THEORETICAL; PLANNING TECHNIQUES; SOFTWARE; SYSTEMS THEORY; WORKPLACE;

EID: 33847661566     PISSN: 10834419     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSMCB.2006.883272     Document Type: Article

References (42)

1. H. Stadtler, "Supply chain management and advanced planning-basics, overview and challenges," Eur. J. Oper. Res., vol. 163, no. 3, pp. 575-588, Jun. 2005.
2. L. Wang, Shop Scheduling with Genetic Algorithms. Beijing, China: Tsinghua Univ. Press, 2003.
3. M. Pinedo, Scheduling: Theory, Algorithms and Systems, 2nd ed. Englewood Cliffs, NJ: Prentice-Hall, 2002.
4. M. R. Garey and D. S. Johnson, Computers and Intractability: A Guide to the Theory of NP-Completeness. San Francisco, CA: Freeman, 1979.
5. S. M. Johnson, "Optimal two-and three-stage production schedules with setup times included," Nav. Res. Logist. Q., vol. 1, no. 1, pp. 61-68, Mar. 1954.
6. R. Ruiz and C. Maroto, "A comprehensive review and evaluation of permutation flowshop heuristics," Eur. J. Oper. Res., vol. 165, no. 2, pp. 479-494, Sep. 2005.
7. B. J. Lageweg, J. K. Lenstra, and A. H. G. Rinnooy Kan, "A general bounding scheme for the permutation flow-shop problem," Oper. Res., vol. 26, no. 1, pp. 53-67, 1978.
8. P. Moscato, "On evolution, search, optimization, genetic algorithms and martial arts: Toward memetic algorithms," in "Caltech Concurrent Computation Program," California Inst. Technol., Pasadena, CA, Tech. Rep. 826, 1989.
9. M. Nawaz, E. Enscore, and I. Ham, "A heuristic algorithm for the m-machine, n-job flow-shop sequencing problem," Omega, vol. 11, no. 1, pp. 91-95, 1983.
10. I. H. Osman and C. N. Potts, "Simulated annealing for permutation flow-shop scheduling," Omega, vol. 17, no. 6, pp. 551-557, 1989.
11. C. R. Reeves, "A genetic algorithm for flowshop sequencing," Comput. Oper. Res., vol. 22, no. 1, pp. 5-13, Jan. 1995.
12. C. R. Reeves and T. Yamada, "Genetic algorithms, path relinking and the flowshop sequencing problem," Evol. Comput., vol. 6, no. 1, pp. 45-60, 1998.
13. E. Nowicki and C. Smutnicki, "A fast tabu search algorithm for the permutation flow-shop problem," Eur. J. Oper. Res., vol. 91, no. 1, pp. 160-175, May 1996.
14. L. Wang and D. Z. Zheng, "A modified evolutionary programming for flow shop scheduling," Int. J. Adv. Manuf. Technol., vol. 22, no. 7/8, pp. 522-527, Nov. 2003.
15. P. Hansen and N. Mladenovic, "Variable neighborhood search: Principles and applications," Eur. J. Oper. Res., vol. 130, no. 3, pp. 449-467, May 2001.
16. L. Wang and D. Z. Zheng, "An effective hybrid heuristic for flow shop scheduling," Int. J. Adv. Manuf. Technol., vol. 21, no. 1, pp. 38-44, 2003.
17. T. Stutzle, "An ant approach to the flow shop problem," in Proc. 6th Eur. Congr. Intell. Tech. and Soft Comput., Aachen, Germany, 1998, pp. 1560-1564.
18. T. Murata, H. Ishibuchi, and H. Tanaka, "Genetic algorithms for flowshop scheduling problems," Comput. Ind. Eng., vol. 30, no. 4, pp. 1061-1071, Sep. 1996.
19. A. C. Nearchou, "A novel metaheuristic approach for the flow shop scheduling problem," Eng. Appl. Artif. Intell., vol. 17, no. 4, pp. 289-300, Apr. 2004.
20. L. Wang, L. Zhang, and D. Z. Zheng, "A class of order-based genetic algorithm for flow shop scheduling," Int. J. Adv. Manuf. Technol., vol. 22, no. 11/12, pp. 828-835, Dec. 2003.
21. W. E. Hart, N. Krasnogor, and J. E. Smith, Recent Advances in Memetic Algorithms. Heidelberg, Germany: Springer-Verlag, 2004.
22. P. Merz, "Memetic algorithms for combinatorial optimization problems: fitness landscapes and effective search strategies," Ph.D. dissertation, Univ. Siegen, Siegen, Germany, 2000.
23. A. Quintero and S. Pierre, "Sequential and multi-population memetic algorithms for assigning cells to switches in mobile networks," Comput. Netw., vol. 43, no. 3, pp. 247-261, Oct. 2003.
24. P. M. França, A. Mendes, and P. Moscato, "A memetic algorithm for the total tardiness single machine scheduling problem," Eur. J. Oper. Res., vol. 132, no. 1, pp. 224-242, Jul. 2001.
25. H. Ishibuchi, T. Yoshida, and T. Murata, "Balance between genetic search and local search in memetic algorithms for multiobjective permutation flowshop scheduling," IEEE Trans. Evol. Comput., vol. 7, no. 2, pp. 204-223, Apr. 2003.
26. M. Milano and A. Roli, "MAGMA: A multiagent architecture for metaheuristics," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 34, no. 2, pp. 925-941, Apr. 2004.
27. N. Krasnogor, "Studies on the theory and design space of memetic algorithms," Ph.D. dissertation, Univ. West England, Bristol, U.K., 2002.
28. Y. S. Ong and A. J. Keane, "Meta-Lamarckian learning in memetic algorithms," IEEE Trans. Evol. Comput., vol. 8, no. 2, pp. 99-110, Apr. 2004.
29. Y. S. Ong, M. H. Lim, N. Zhu, and K. W. Wong, "Classification of adaptive memetic algorithms: A comparative study," IEEE Trans. Syst., Man, Cybern. B, Cybent, vol. 36, no. 1, pp. 141-152, Feb. 2006.
30. Y. S. Ong, P. B. Nair, and A. J. Keane, "Evolutionary optimization of computationally expensive problems via surrogate modeling," AIAA J., vol. 41, no. 4, pp. 687-696, 2003.
31. L. Wang, L. Zhang, and D. Z. Zheng, "A class of hypothesis-test based genetic algorithm for flow shop scheduling with stochastic processing time," Int. J. Adv. Manuf. Technol., vol. 25, no. 11/12, pp. 1157-1163, Jun. 2005.
32. H. Ishibuchi and T. Murata, "A multi-objective genetic local search algorithm and its application to flowshop scheduling," IEEE Trans. Syst., Man, Cybern. C, Appl. Rev., vol. 28, no. 3, pp. 392-403, Aug. 1998.
33. J. Kennedy, R. C. Eberhart, and Y. Shi, Swann Intelligence. San Francisco, CA: Morgan Kaufmann Publishers, 2001.
34. B. Liu, L. Wang, H. Jin, and D. X. Huang, "Advances in particle swarm optimization algorithm," Control Instruments Chemical Industry, vol. 32, no. 3, pp. 1-6, 2005.
35. B. Liu, L. Wang, Y. H. Jin, F. Tang, and D. X. Huang, "Improved particle swarm optimization combined with chaos," Chaos, Solitons Fractals, vol. 25, no. 5, pp. 1261-1271, Sep. 2005.
36. M. F. Tasgetiren, M. Sevkli, Y. C. Liang, and G. Gencyilmaz, "Particle swarm optimization algorithm for permutation flowshop sequencing problem," in Lecture Notes in Computer Science, vol. 3172, M. Dorigo, M. Birattari, and C. Blum, Eds. New York: Springer-Verlag, 2004, pp. 382-389.
37. J. C. Bean, "Genetic algorithms and random keys for sequencing and optimization," ORSA J. Comput., vol. 6, no. 2, pp. 154-160, 1994.
38. T. Aldowaisan and A. Allahverdi, "New heuristics for no-wait flowshops to minimize makespan," Comput. Oper Res., vol. 30, no. 8, pp. 1219-1231, Jul. 2003.
39. D. E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning. Reading, MA: Addison-Wesley, 1989.
40. S. Kirkpatrick, C. D. Gelat, and M. P. Vecchi, "Optimization by simulated annealing," Science, vol. 220, no. 4598, pp. 671-680, 1983.
41. L. Wang and D. Z. Zheng, "An effective hybrid optimization strategy for job-shop scheduling problems," Comput. Oper. Res., vol. 28, no. 6, pp. 585-596, May 2001.
42. J. Carlier, "Ordonnancements a contraintes disjonctives," R.A.I.R.O. Recherche Operationelle/Oper. Res., vol. 12, no. 4, pp. 333-351, 1978.