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Flow Shop Scheduling Problems Under Uncertainty Based on Fuzzy Cut-Set

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Advances in Natural Computation (ICNC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3611))

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Abstract

Production scheduling is an important part in the factories, and there are various uncertainties in the production scheduling of industrial processes. A scheduling mathematical model for flow shop problems with uncertain processing time has been established based on fuzzy programming theory. And in this paper, the fuzzy model can be translated into two mathematical models about the characteristic of scheduling problems. Furthermore, a fuzzy immune scheduling algorithm combined with the feature of the Immune Algorithm is proposed, which prevents the possibility of stagnation in the iteration process and achieves fast convergence for global optimization. The effectiveness and efficiency of the fuzzy scheduling model and the proposed algorithm are demonstrated by simulation results.

This work was supported by the National Natural Science Foundation of China (Grant No.60474043) and The Key Technologies Program of Shanghai Municipal Science and Technology Commission (Grant No. 04dz11008).

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© 2005 Springer-Verlag Berlin Heidelberg

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Xu, Z., Gu, X. (2005). Flow Shop Scheduling Problems Under Uncertainty Based on Fuzzy Cut-Set. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539117_124

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