Abstract
A job shop scheduling problem with fuzzy due dates is discussed. The membership function of a fuzzy due date assigned to each job denotes the degree of satisfaction of a decision maker for the completion time of this job. The performance criterion of proposed problem is to maximize the minimum degree of satisfaction over given jobs, and it is an NP-complete problem. Thus artificial neural network is considered to search optimal jobs schedule.
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Ishii, H., Tada, M., Masuda, T.: Two Scheduling Problems with Fuzzy Due-dates. Fuzzy Sets and Systems 46, 339–347 (1992)
Han, S., Ishii, H., Fujii, S.: One Machine Scheduling System with Fuzzy Duedates. European Journal Operational Research 79, 1–12 (1994)
Foo, Y.S., Takefuji, Y.: Integer Linear Programming Neural Networks for Job Shop Scheduling. In: Proc. IEEEI JCNN, vol. 2, pp. 341–348. IEEE, San Diego (1988)
Looi, C.: Neural Network Methods in Combinatorial Optimization. Computers and Operations Research 19, 191–208 (1992)
Zhang, C.S., Yan, P.F.: Neural Network Method of Solving Job Shop Scheduling Problem. ACTA Automation Sinica 21, 706–712 (1995)
Fisher, H., Thompson, G.L.: Probabilistic Learning Combinations of Local Job shop Scheduling Rules. In: Muth, J., Thompson, G. (eds.) Industrial Scheduling, pp. 225–251. Prentice Hall, Englewood Cliffs (1963)
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© 2005 Springer-Verlag Berlin Heidelberg
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Xie, Y., Xie, J., Li, J. (2005). Fuzzy Due Dates Job Shop Scheduling Problem Based on Neural Network. In: Wang, J., Liao, X., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3496. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427391_125
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DOI: https://doi.org/10.1007/11427391_125
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25912-1
Online ISBN: 978-3-540-32065-4
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