articleIEEE Transactions on Industrial InformaticsApr 7, 2022Closed access

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

GWGai‐Ge WangDGDa GaoWPWitold Pedrycz

Ocean University of China · University of Alberta · +3 more institutions

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Abstract

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 processing time and completion time (FJSP) can model the scheduling more comprehensively, which benefits from the developments of fuzzy sets. Fuzzy relative entropy leads to a method that can evaluate the quality of a feasible solution following the comparison between the actual value and the ideal value (the due date). Therefore, the multiobjective FJSP can be transformed into a single-objective optimization problem…

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Topics & keywords

Topics
Keywords
  • Job shop scheduling
  • Scheduling (production processes)
  • Fuzzy logic
  • Mathematical optimization
  • Computer science
  • Algorithm
  • Population
  • Differential evolution
UN Sustainable Development Goals
  • Affordable and clean energy
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