Simultaneous scheduling of production and maintenance tasks in the job shop

International Journal of Production Research

Volumn 49, Issue 13, 2011, Pages 3891-3918

  Ben Ali, M ^a,b   Sassi, M ^b   Gossa, M ^b   Harrath, Y ^c  

^a UNIVERSITY OF GAFSA   (Tunisia)

^b UNIVERSITY OF TUNIS   (Tunisia)

^c UNIVERSITY OF HAIL   (Saudi Arabia)

Author keywords

GA parameters; job shop; lower bounds; maintenance; multi objective genetic algorithms; scheduling

Indexed keywords

COMPUTATIONAL EXPERIMENT; GA PARAMETERS; JOB SHOP; JOB SHOP PROBLEM; LOWER BOUNDS; MAINTENANCE COST; MAINTENANCE TASKS; MAKESPAN; MULTI-OBJECTIVE GENETIC ALGORITHM; PARETO OPTIMAL SOLUTIONS; PRODUCTION OPERATIONS; SIMULTANEOUS SCHEDULING;

COMPUTATIONAL EFFICIENCY; GENETIC ALGORITHMS; MAINTAINABILITY; MATHEMATICAL OPERATORS; MULTIOBJECTIVE OPTIMIZATION; SCHEDULING ALGORITHMS;

PREVENTIVE MAINTENANCE;

EID: 79957490775     PISSN: 00207543     EISSN: 1366588X     Source Type: Journal    
DOI: 10.1080/00207543.2010.492405     Document Type: Article

References (53)

1. Aggoune, R., 2004. Two-job shop scheduling problems with availability constraints. In: Proceedings of the fourteenth international conference on automated planning and scheduling ICAPS 2004, 3-7 June, Whistler, Canada, 253-259. (Pubitemid 40201852)
2. Batun, S. and Azizolu, M., 2009. Single machine scheduling with preventive maintenances. International Journal of Production Research, 47 (7), 1753-1771.
3. Ben Ali, M., et al., 2007. Evaluation des coǔts de maintenance d'un probléme d'ordonnancement conjoint de production et de maintenance de type job shop. In: Proceedings of 3e Congrés Performances et Nouvelles TechnOlogies en Maintenance PENTOM 2007, 9-10 July, Mons, Belgium.
4. Benbouzid, F., Varnier, C., and Zerhouni, N., 2003. Resolution of joint maintenance/production scheduling by sequential and integrated strategies. In: Artificial neural nets problem solving methods (LNCS vol. 2687). Berlin: Springer, 782-789.
5. Breit, J., 2004. An improved approximation algorithm for two-machine flow shop scheduling with an availability constraint. Information Processing Letters, 90 (6), 273-278.
6. Cassady, C.R. and Kutanoglu, E., 2003. Minimizing job tardiness using integrated preventive maintenance planning and production scheduling. IEE Transactions, 35 (6), 503-513.
7. Castanier, B., Grall, A., and Bérenguer, C., 2005. A condition-based maintenance policy with nonperiodic inspections for a two-unit series system. Reliability Engineering and System Safety, 87 (1), 109-120.
8. Cavory, G., Dupas, R., and Goncalves, G., 2001. A genetic approach to the scheduling of preventive maintenance tasks on a single product manufacturing production line. International Journal of Production Economics, 74 (1-3), 135-146. (Pubitemid 32998199)
9. Chan, F.T.S., 2006. Solving distributed FMS scheduling problems subject to maintenance: Genetic algorithms approach. Robotics and Computer-Integrated Manufacturing, 22 (5-6), 493-504. (Pubitemid 44175755)
10. Chareonsuk, C., Nagarur, N., and Tabucanon, M.T., 1997.Amulticriteria approach to the selection of preventive maintenance intervals. International Journal of Production Economics, 49 (1), 55-64. (Pubitemid 127412304)
11. Chen, J.S., 2008. Scheduling of nonresumable jobs and flexible maintenance activities on a single machine to minimize makespan. European Journal of Operational Research: Discrete Optimization, 190 (1), 90-102.
12. Cheng, T.C.E. and Wang, G., 2000. An improved heuristic for two-machine flowshop scheduling with an availability constraint. Operations Research Letters, 26 (5), 223-229.
13. Chung, S.H., Chan, F.T.S., and Chan, H.K., 2009. A modified genetic algorithm approach for scheduling of perfect maintenance in distributed production scheduling. Engineering Application of Artificial Intelligence, 22 (7), 1005-1014.
14. Coudert, T., Grabot, B., and Archiméde, B., 2002. Production/maintenance cooperative scheduling using multi-agents and fuzzy logic. International Journal of Production Research, 40 (18), 4611-4632.
15. Deb, K., 2003. Multi-objective evolutionary algorithms: Introducing bias among Pareto-optimal solutions. Advances in evolutionary computing: Theory and applications. Berlin: Springer, 263-292.
16. Fisher, H. and Thompson, G.L., 1963. Probabilistic learning combinations of local job-shop scheduling rules. In: J.F. Muth and G.L. Thompson, eds. Industrial Scheduling. Englewood Cliffs, New Jersey: Prentice-Hall, 225-251.
17. Fonseca, C.M. and Fleming, P.J., 1993. Genetic algorithms for multiobjective optimization: Formulation, discussion, and generalization. In: Proceedings of the fifth international conference on genetic algorithms, 17-21, July Urbana-Champaign, IL. San Mateo, CA: Morgan Kaufmann, 416-423.
18. Frickenstein, S.G. and Whitaker, L.R., 2003. Age replacement policies in two time scales. Naval Research Logistics, 50 (6), 592-613.
19. Gharbi, A., Beauchamp, Y., and Andriamaharosoa, S., 2001. Stratégie de maintenance préventive de type ǎge : Approche basée sur l'intégration de la simulation et des plans d'expérience. In: Proceedings of 3e Conférence Francophone de MOdélisation et SIMulation 'Conception, Analyse et Gestion des Systémes Industriels' MOSIM'01, 25-27 April, Troyes, France, 797-803.
20. Glade, M., Longere, J.Y., and Lyonnet, P., 2002. Design of parametric maintenance cost models. In: Proceedings of the IEEE international conference on systems, man and cybernetics, vol. 3, 6-9 October Hammamet, Tunisia, 6, 01-07.
21. Goldberg, D., 1989. Genetic algorithm in search, optimisation & machine learning. Reading, MA: Addison Wesley.
22. Gonçalves, J.F., Mendes, J.J.M., and Resende, M.G.C., 2005. A hybrid genetic algorithm for the job shop scheduling problem. European Journal of Operational Research, 167 (1), 73-95.
23. Gurel, S. and Selim Akturk, M., 2008. Scheduling preventive maintenance on a single CNC machine. International Journal of Production Research, 46 (24), 6797-6821.
24. Harrath, Y., Chebel-Morello, B., and Zerhouni, N., 2003. Lower bounds and multiobjective evolutionary optimization for combined maintenance and production scheduling in job shop. In: Proceedings of the 9th IEEE international conference on emerging technologies and factory automation, ETFA'03, 16-17 September, Lisbon, Portugal, 2, 95-100.
25. Kaabi, J., Varnier, C., and Zerhouni, N., 2003. Scheduling with machine availability: An integrated approach. In: Proceedings of the international conference on industrial engineering and production management, IEPM'03, 26-28 May, Porto, Portugal.
26. Kacem, I., Hammadi, S., and Borne, P., 2002. Pareto-optimality approach for flexible job-shop scheduling problems: Hybridisation of evolutionary algorithms and fuzzy logic. Journal of Mathematics and Computers in Simulation, 60 (3-5), 245-276.
27. Kubiak, W., et al., 2002. Two-machine flow shops with limited machine availability. European Journal of Operational Research: Discrete Optimization, 136 (3), 528-540. (Pubitemid 33094119)
28. Kuo, Y. and Chang, Z.A., 2007. Integrated production scheduling and preventive maintenance planning for a single machine under a cumulative damage failure process. Naval Research Logistics, 54 (6), 602-614. (Pubitemid 47395706)
29. Landa Silva, J.D., Burke, E., and Petrovic, S., 2004. An introduction to multiobjective metaheuristics for scheduling and timetabling. In: Metaheuristics for multiobjective optimisation (Lecture notes in economics and mathematical systems vol. 535). Berlin: Springer, 91-132. (Pubitemid 38203478)
30. Lawrence, S., 1984. Resource constrained project scheduling: An experimental investigation of heuristic scheduling techniques. Graduate School of Administration, Carregie-Mellon University, Pittsburgh, PA, USA.
31. Lee, C.Y., 1999. Two-machine flowshop scheduling with availability constraints. European Journal of Operational Research: Theory and Methodology, 114 (2), 420-429.
32. Lee, C.Y. and Lin, C.S., 2001. Single-machine scheduling with maintenance and repair ratemodifying activities. European Journal of Operational Research: Theory and Methodology, 135 (3), 493-513.
33. Mahdavi, M. and Mahdavi, M., 2009. Optimization of age replacement policy using reliability based heuristic model. Journal of Scientific & Industrial Research, 68 (8), 668-673.
34. Mattfeld, D.C. and Bierwirth, C., 2004. An efficient genetic algorithm for job shop scheduling with tardiness objectives. European Journal of Operational Research, 155 (3), 616-630.
35. Murata, T., 1997. Genetic algorithms for multi-objective optimization. Thesis (PhD). Osaka Prefecture University. Japan.
36. Naderi, B., Zandieh, M., and Fatemi Ghomi, S.M.T., 2009. Scheduling sequence-dependent setup time job shops with preventive maintenance. International Journal of Advanced Manufacturing Technology, 43 (1-2), 170-181.
37. Nawaz, M., Enscore Jr., E., and Ham, I., 1983. A heuristic algorithm for the m-machine, n-job flow-shop sequencing problem. Omega, The International Journal of Management Science, 11 (1), 91-95. (Pubitemid 13193807)
38. Neef, M., Thierens, D., and Arciszewski, H., 1999. A case study of a multiobjective elitist recombinative genetic algorithm with coevolutionary sharing. In: P Angeline, ed. Proceedings of the international congress on evolutionary computation. Piscataway, NJ: IEEE Press, 796-803.
39. Nicolai, R.P., 2008. Maintenance models for systems subject to measurable deterioration. Thesis (PhD). Erasmus University, Rotterdam.
40. O'Donoghue, C.D. and Prendergast, J.G., 2004. Implementation and benefits of introducing a computerised maintenance management system into a textile manufacturing company. Journal of Materials Processing Technology, 153-154, 226-232.
41. Ponnambalam, S.G., Aravindan, P., and Sreenivasa Rao, P., 2001. Comparative evaluation of genetic algorithms for job-shop scheduling. Production Planning & Control, 12 (12), 560-574. (Pubitemid 35395059)
42. Ruiz, R., Garcia-Diaz, C., and Maroto, C., 2007. Considering scheduling and preventive maintenance in the flowshop sequencing problem. Computers & Operations Research, 34 (11), 3314-330. (Pubitemid 46517859)
43. Sortrakul, N., Nachtmann, H.L., and Cassady, C.R., 2005. Genetic algorithms for integrated preventive maintenance planning and production scheduling for single machine. Computers in Industry, 56 (2), 161-168. (Pubitemid 40206234)
44. Sortrakul, N. and Cassady, C.R., 2007. Genetic algorithms for total weighted expected tardiness integrated preventive maintenance planning and production scheduling for a single machine. Journal of Quality in Maintenance Engineering, 13 (1), 49-61. (Pubitemid 46432522)
45. Wang, H., 2002. A survey of maintenance policies of deteriorating systems. European Journal of Operational Research, 139 (3), 469-489. (Pubitemid 34249626)
46. Wang, L., Chu, J., and Mao, W., 2008. A condition-based order-replacement policy for a single-unit system. Applied Mathematical Modelling, 32 (11), 2274-2289.
47. Wang, X. and Cheng, T.C.E., 2007. Heuristics for two-machine flowshop scheduling with setup times and an availability constraint. Computers & Operations Research, 34 (1), 152-162. (Pubitemid 44093846)
48. Wang, Y., Cheu, R.L., and Fwa, T.F., 2002. Highway maintenance scheduling using genetic algorithm with microscopic traffic simulation. In: Proceedings of the 81st annual meeting of the Transportation Research Board (TRB), 13-17 January, Washington, DC, paper no. 02-2174.
49. Wildeman, R.E., Dekker, R., and Smit, A.C.J.M., 1997. A dynamic policy for grouping maintenance activities. European Journal of Operational Research, 99 (3), 530-551. (Pubitemid 127416269)
50. Woods, G.W., 1997. A hybrid genetic algorithm that adapts to binary and real coded operators. Thesis (Minor). Department of Computer Science, RMIT.
51. Yamada, T. and Nakano, R., 1997. Genetic algorithms for job-shop scheduling problems. In: Proceedings of modern heuristic for decision support, 18-19 March, London, UK, 67-81.
52. Zhang, C.Y., et al., 2008. A very fast TS/SA algorithm for the job shop scheduling problem. Computers & Operations Research, 35 (1), 282-294. (Pubitemid 46899361)
53. Zribi, N., El Kamel, A., and Borne, P., 2008. Minimizing the makespan for the MPM job-shop with availability constraints. International Journal of Production Economics, 112 (1), 151-160. (Pubitemid 351179597)