Job shop scheduling - Open Access .click

IEEE Transactions on Evolutionary Computation, 2023
Green flexible job-shop scheduling problem (FJSP) aims to improve profit and reduce energy consumption for modern manufacturing. Meanwhile, FJSP with type-2 fuzzy processing time is proposed to predict the uncertainty in timing constraint for better ...
Rui Li, Wenyin Gong, Chao Lu, Ling Wang
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A Deep Reinforcement Learning Framework Based on an Attention Mechanism and Disjunctive Graph Embedding for the Job-Shop Scheduling Problem

IEEE Transactions on Industrial Informatics, 2023
The job-shop scheduling problem (JSSP) is a classical NP-hard combinatorial optimization problem, and the operating efficiency of manufacturing system is affected directly by the quality of its scheduling scheme.
R. Chen, Wenxin Li, Hongbin Yang
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Dynamic Job-Shop Scheduling Problems Using Graph Neural Network and Deep Reinforcement Learning

IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2023
The job-shop scheduling problem (JSSP) is one of the best-known combinatorial optimization problems and is also an essential task in various sectors.
Chien-Liang Liu, Tzu-Hsuan Huang
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Solving Multiobjective Fuzzy Job-Shop Scheduling Problem by a Hybrid Adaptive Differential Evolution Algorithm

IEEE Transactions on Industrial Informatics, 2022
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 ...
Gai-ge Wang, D. Gao, W. Pedrycz
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scheduling production processes
mathematics
mathematical optimization

operating system
schedule
flow shop scheduling

job shop
artificial intelligence
algorithm