Results 11 to 20 of about 1,901,812 (345)
Learning to schedule job-shop problems: representation and policy learning using graph neural network and reinforcement learning [PDF]
International Journal of Production Research, 2021 We propose a framework to learn to schedule a job-shop problem (JSSP) using a graph neural network (GNN) and reinforcement learning (RL). We formulate the scheduling process of JSSP as a sequential decision-making problem with graph representation of the
Junyoung Park +4 more
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Flexible Job-Shop Scheduling via Graph Neural Network and Deep Reinforcement Learning
IEEE Transactions on Industrial Informatics, 2023 Recently, deep reinforcement learning (DRL) has been applied to learn priority dispatching rules (PDRs) for solving complex scheduling problems. However, the existing works face challenges in dealing with flexibility, which allows an operation to be ...
Wen Song +3 more
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Deep Reinforcement Learning for Dynamic Flexible Job Shop Scheduling with Random Job Arrival
Processes, 2022 The production process of a smart factory is complex and dynamic. As the core of manufacturing management, the research into the flexible job shop scheduling problem (FJSP) focuses on optimizing scheduling decisions in real time, according to the changes
Jingru Chang +4 more
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Solving flexible job shop scheduling problems in manufacturing with Quantum Annealing
Production Engineering, 2022 Quantum Annealing (QA) is a metaheuristic for solving optimization problems in a time-efficient manner. Therefore, quantum mechanical effects are used to compute and evaluate many possible solutions of an optimization problem simultaneously.
Philipp Schworm +3 more
semanticscholar +1 more source
A precedence constrained flow shop scheduling problem with transportation time, breakdown times, and weighted jobs [PDF]
Journal of Project Management, 2022 Job precedence can often be seen in various manufacturing process scenarios. For instance, in the context of flow shop scheduling, certain jobs must be processed before a specific job may be executed.
M. Thangaraj +2 more
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IEEE Transactions on Evolutionary Computation, 2021 Dynamic flexible job shop scheduling (JSS) is an important combinatorial optimization problem with complex routing and sequencing decisions under dynamic environments.
Fangfang Zhang +4 more
semanticscholar +1 more source
The Comparison of the Integer Programming Models for Solving the Stage Shop Scheduling Problem [PDF]
مجله مدل سازی در مهندسی, 2018 The development and extending the classic models for approaching the real world conditions are always in consideration of researchers. For this reason, many efforts are made for generalization of the job shop scheduling problem. The stage shop scheduling
Mohammad Mahdi Nasiri
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Applied Sciences, 2023 Gene expression programming (GEP) is frequently used to create intelligent dispatching rules for job-shop scheduling. The proper selection of the terminal set is a critical factor for the success of GEP.
Adilanmu Sitahong +4 more
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Applying flexible job shop scheduling in patients management to optimize processing time in hospitals. [PDF]
International Journal of Research in Industrial Engineering, 2021 The continuous growth of the population causes an increased demand for our healthcare services. Insufficient hospitals face challenges to serve the patient within a preferable duration.
N. Sarfaraj, Md. L. Lingkon, N. Zahan
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EURASIP Journal on Wireless Communications and Networking, 2018 Reasonable scheduling of flexible job shop is key to improve production efficiency and economic benefits; in order to solve the problem in flexible job shop scheduling problem, a novel flexible job shop scheduling method based on improved artificial ...
Rui Zeng, Yingyan Wang
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