Solving Multiobjective Fuzzy Job-Shop Scheduling Problem by a Hybrid Adaptive Differential Evolution Algorithm

The job-shop scheduling problem (JSP) is NP hard, which has very important practical significance. Because of many uncontrollable factors, such as machine delay or human factors, it is difficult to use a single real-number to express the processing and completion time of the jobs. JSP with fuzzy pro...

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Bibliographic Details
Published in:	IEEE transactions on industrial informatics Vol. 18; no. 12; pp. 8519 - 8528
Main Authors:	Wang, Gai-Ge, Gao, Da, Pedrycz, Witold
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 01.12.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Adaptive algorithms Adaptive parameter control Algorithms Ant colony optimization Completion time Delay time differential evolution Energy consumption Entropy Evolutionary algorithms Evolutionary computation fuzzy processing and date time Fuzzy sets fuzzy sets theory Genetic algorithms Human factors HyperText Markup Language Job shop scheduling Mutation Optimization Particle swarm optimization Scheduling selection mechanism Sociology Statistics
ISSN:	1551-3203, 1941-0050
Online Access:	Get full text
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