Local search and genetic algorithm for the job shop ...

1 downloads 0 Views 147KB Size Report
Camino R. Vela · Ramiro Varela ·. Miguel A. González. Received: 28 February 2007 / Revised: 2 June 2008 / Accepted: 12 August 2008 /. Published online: 30 ...
J Heuristics (2010) 16: 139–165 DOI 10.1007/s10732-008-9094-y

Local search and genetic algorithm for the job shop scheduling problem with sequence dependent setup times Camino R. Vela · Ramiro Varela · Miguel A. González Received: 28 February 2007 / Revised: 2 June 2008 / Accepted: 12 August 2008 / Published online: 30 September 2008 © Springer Science+Business Media, LLC 2008

Abstract The Job Shop Scheduling Problem (JSP) is an example of a combinatorial optimization problem that has interested researchers for several decades. In this paper we confront an extension of this problem called JSP with Sequence Dependent Setup Times (SDST-JSP). The approach extends a genetic algorithm and a local search method that demonstrated to be efficient in solving the JSP. For local search, we have formalized neighborhood structures that generalize three well-know structures defined for the JSP. We have conducted an experimental study across conventional benchmark instances showing that the genetic algorithm exploited in combination with the local search, considering all three neighborhoods at the same time, provides the best results. Moreover, this approach outperforms the current state-ofthe-art methods. Keywords Genetic algorithms · Local search · Job shop scheduling · Setup times

Introduction The Job Shop Scheduling Problem with Sequence Dependent Setup Times (SDSTJSP) is a generalization of the classical Job Shop Scheduling Problem (JSP) in which a setup operation on a machine is required when the machine switches between two jobs. In this way the SDST-JSP models many real situations better than the JSP. C.R. Vela · R. Varela () · M.A. González Computing Technologies Group, Department of Computing, Artificial Intelligence Center, University of Oviedo, Campus of Viesques, 33271 Gijón, Spain e-mail: [email protected] C.R. Vela e-mail: [email protected] M.A. González e-mail: [email protected]

Local search and genetic algorithm for the job shop scheduling

165

González, M., Sierra, M., Vela, C., Varela, R.: Genetic algorithms hybridized with greedy algorithms and local search over the spaces of active and semi-active schedules. In: Current Topics in Artificial Intelligence. 11th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2005. LNCS, vol. 4177, pp. 231–240. Springer, Berlin (2006a). Revised Selected Papers González, M., Sierra, M., Vela, C., Varela, R., Puente, J.: Combining metaheuristics for the job shop scheduling problem with sequence dependent setup times. In: Proceedings of the First International Conference on Software and Data Technologies, ICSOFT’2006, pp. 211–220 (2006b) Holland, J.H.: Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence. The University of Michigan Press, Ann Arbor (1975) Ives, P., Lambrecht, M.: Extending the shifting bottleneck procedure to real-life applications. Eur. J. Oper. Res. 90(3), 252–268 (1996) Jain, A.S., Rangaswarny, B., Meeran, S.: New and “stronger” job-shop neighbourhoods: A focus on the method of Nowicki and Smutnicki (1996). J. Heuristics 6(4), 457–480 (2000) Kim, S., Bobrowski, P.: Impact of sequence-dependent setup time on job shop scheduling performance. Int. J. Prod. Res. 32(7), 1503–1520 (1994) Lawrence, S.: Resource constrained project scheduling: an experimental investigation of heuristic scheduling techniques (supplement). Technical Report, Graduate School of Industrial Administration, Carnegie Mellon University (1984) Matsuo, H., Suh, C., Sullivan, R.: A controlled search simulated annealing method for the general jobshop scheduling problem. Working Paper 03-44-88, Graduate School of Business, University of Texas (1988) Mattfeld, D.: Evolutionary Search and the Job Shop. Investigations on Genetic Algorithms for Production Scheduling. Springer, Berlin (1995) Michalewicz, Z.: Genetic Algorithms + Data Structures = Evolution Program, 2nd, Extended edn Springer, Berlin (1994) Miller, D., Chen, H.-C., Matson, J., Liu, Q.: A hybrid genetic algorithm for the single machine scheduling problem. J. Heuristics 5(4), 437–454 (1999) Mönch, L., Schabacker, R., Pabst, D., Fowler, J.: Genetic algorithm-based subproblem solution procedures for a modified shifting bottleneck heuristic for complex job shops. Eur. J. Oper. Res. 177(3), 2100– 2118 (2007) Noivo, A., Ramalhinho-Lourenço, H.: Solving two production scheduling problems with sequencedependent set-up times. Technical Report 138, Department of Economic and Business, Universitat Pompeu Fabra, Barcelona (1998) Nowicki, E., Smutnicki, C.: A fast taboo search algorithm for the job shop problem. Manag. Sci. 42, 797–813 (1996) Rios-Mercado, R.Z., Bard, J.F.: An enhanced tsp-based heuristic for makespan minimization in a floor shop with setup times. J. Heuristics 5(1), 53–70 (1999) Roy, B., Sussmann, B.: Les problèmes d’ordonnancement avec constraintes disjonctives. Note DS n.6 bis, SEMA, Matrouge, 6 (1964) Taillard, E.: Parallel taboo search techniques for the job shop scheduling problem. ORSA J. Comput. 6, 108–117 (1993) Van Laarhoven, P., Aarts, E., Lenstra, K.: Job shop scheduling by simulated annealing. ORSA J. Comput. 40, 113–125 (1992) Varela, R., Vela, C., Puente, J., Gomez, A.: A knowledge-based evolutionary strategy for scheduling problems with bottlenecks. Eur. J. Oper. Res. 145, 57–71 (2003) Varela, R., Serrano, D., Sierra, M.: New codification schemas for scheduling with genetic algorithms. In: Proceedings of the First International Work-conference on the Interplay between Natural and Artificial Computation, IWINAC 2005. LNCS, vol. 3562, pp. 11–20. Springer, Berlin (2005) Wilbrech, J., Prescott, W.: The influence of setup time on job shop performance. Manag. Sci. 16(4), 391– 401 (1969) Yamada, T., Nakano, R.: Scheduling by genetic local search with multi-step crossover. In: Fourth Int. Conf. on Parallel Problem Solving from Nature (PPSN IV), pp. 960–969 (1996) Zhou, Y., Li, B., Yang, J.: Study on job shop scheduling with sequence-dependent setup times using biological immune algorithm. Int. J. Adv. Manuf. Technol. 30(1–2), 105–111 (2006) Zoghby, J., Barnes, J., J.J., H.: Modeling the re-entrant job shop scheduling problem with setup for metaheuristic searches. Eur. J. Oper. Res. 167, 336–348 (2005)