Solving fuzzy flexible job shop scheduling problem based on fuzzy satisfaction rate and differential evolution

Focused on a variety of JSSP considered flexibility and fuzziness, namely the fuzzy flexibility JSSP (FfJSSP), a novel method based on fuzzy satisfaction rate and differential evolution (DE) algorithm is proposed in this paper. In the method, the fuzzy membership functions' parameters are deter...

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Bibliographic Details
Published in:Advances in production engineering & management 2018-03, Vol.13 (1), p.44-56
Main Authors: Ma, D.Y., He, C.H., Wang, S.Q., Han, X.M., Shi, X.H.
Format: Article
Language:English
Subjects:
Coding
Evolutionary algorithms
Flexibility
Job shop scheduling
Job shops
Normal distribution
Operators (mathematics)
Performance enhancement
Production scheduling
Online Access:Get full text
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Summary:Focused on a variety of JSSP considered flexibility and fuzziness, namely the fuzzy flexibility JSSP (FfJSSP), a novel method based on fuzzy satisfaction rate and differential evolution (DE) algorithm is proposed in this paper. In the method, the fuzzy membership functions' parameters are determined according to normal distribution for maximum satisfaction rate calculation. Then a DE algorithm is proposed by well designing the coding for the problem and extending the related operators on the coding. A local exploring search for operation and machine parts of the coding is also introduced to improve the performance of the method. Experimental results show that our proposed method is effective compared with other five popular existed methods. Comparisons between different mutation and crossover strategies are also performed. Numerical results show that the proposed method could be applied to real FfJSSP problems.
ISSN:1854-6250
1855-6531
DOI:10.14743/apem2018.1.272