An efficient search method for multi-objective flexible job shop scheduling problems

Flexible job shop scheduling is very important in both fields of production management and combinatorial optimization. Owing to the high computational complexity, it is quite difficult to achieve an optimal solution to this problem with traditional optimization approaches. Motivated by some empirica...

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Bibliographic Details
Published inJournal of intelligent manufacturing Vol. 20; no. 3; pp. 283 - 293
Main Authors Xing, Li-Ning, Chen, Ying-Wu, Yang, Ke-Wei
Format Journal Article
LanguageEnglish
Published Boston Springer US 01.06.2009
Springer Nature B.V
Subjects
Business and Management
Control
Employment
Flexible manufacturing systems
Genetic algorithms
Heuristic
Intelligent systems
Job shops
Machine learning
Machines
Manufacturing
Mechatronics
Optimization
Optimization algorithms
Processes
Production
Production management
Production scheduling
Robotics
Scheduling
Studies
Workloads
Production schedules
Local search
Multi-objective optimization
Flexible jobshop scheduling
Combinatorial optimization
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Summary:Flexible job shop scheduling is very important in both fields of production management and combinatorial optimization. Owing to the high computational complexity, it is quite difficult to achieve an optimal solution to this problem with traditional optimization approaches. Motivated by some empirical knowledge, we propose an efficient search method for the multi-objective flexible job shop scheduling problems in this paper. Through the work presented in this work, we hope to move a step closer to the ultimate vision of an automated system for generating optimal or near-optimal production schedules. The final experimental results have shown that the proposed algorithm is a feasible and effective approach for the multi-objective flexible job shop scheduling problems.
ISSN:0956-5515
1572-8145
DOI:10.1007/s10845-008-0216-z