Abstract
We study a two-machine re-entrant flowshop scheduling problem in which the jobs have strict due dates. In order to be able to satisfy all customers and avoid any tardiness, scheduler decides which job shall be outsourced and find the best sequence for in-house jobs. Two objective functions are considered: minimizing total completion time for in-house jobs and minimizing outsource cost for others. Since the problem is NP-hard, an efficient genetic algorithm based on modified self-control dominance concept with adaptive generation size is proposed. Non-dominated solutions are compared with classical NSGA-II regarding different metrics. The results indicate the ability of our proposed algorithm to find a good approximation of the middle part of the Pareto front.
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References
Danping, L., Lee, C.K.M.: A review of the research methodology for the re-entrant scheduling problem. International Journal of Production Research 49(8), 2221–2242 (2011)
Slotnick, S.A.: Order acceptance and scheduling: A taxonomy and review. European Journal of Operational Research 212, 1–11 (2011)
Gonzalez, T., Sahni, S.: Flowshop and jobshop schedules: complexity and approximations. Operations Research 26(1), 36–52 (1978)
Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transaction on Evolutionary Computation 6(2), 182–197 (2002)
Sato, H., Aguirre, H.E., Tanaka, K.: Self-Controlling Dominance Area of Solutions in Evolutionary Many-Objective Optimization. In: Deb, K., Bhattacharya, A., Chakraborti, N., Chakroborty, P., Das, S., Dutta, J., Gupta, S.K., Jain, A., Aggarwal, V., Branke, J., Louis, S.J., Tan, K.C. (eds.) SEAL 2010. LNCS, vol. 6457, pp. 455–465. Springer, Heidelberg (2010)
Dugardin, F., Yalaoui, F., Amodeo, L.: New multi-objective method to solve re-entrant hybrid flow shop scheduling problem. European Journal of Operational Research 203, 22–31 (2010)
Choi, S.W., Kim, Y.D.: Minimizing total tardiness on a two-machine re-entrant flowshop. European Journal of Operational Research 199, 375–384 (2009)
Tan, K.C., Lee, T.H., Khor, E.F.: Evolutionary algorithms with dynamic population size and local exploration for multiobjective optimization. IEEE Transactions on Evolutionary Computation 5(6), 565–588 (2001)
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© 2012 Springer-Verlag Berlin Heidelberg
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Moghaddam, A., Yalaoui, F., Amodeo, L. (2012). An Efficient Meta-heuristic Based on Self-control Dominance Concept for a Bi-objective Re-entrant Scheduling Problem with Outsourcing. In: Hamadi, Y., Schoenauer, M. (eds) Learning and Intelligent Optimization. LION 2012. Lecture Notes in Computer Science, vol 7219. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34413-8_46
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DOI: https://doi.org/10.1007/978-3-642-34413-8_46
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34412-1
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