Results 1 to 10 of about 82,206 (311)
A permutation procedure for job-shop scheduling [PDF]
The Computer Journal, 1968 Tony Nicholson, R. D. Pullen
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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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A case study of variational quantum algorithms for a job shop scheduling problem [PDF]
EPJ Quantum Technology, 2021 Combinatorial optimization models a vast range of industrial processes aiming at improving their efficiency. In general, solving this type of problem exactly is computationally intractable.
D. Amaro +4 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
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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
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Improved Artificial Immune System Algorithm for Type-2 Fuzzy Flexible Job Shop Scheduling Problem
IEEE transactions on fuzzy systems, 2021 In practical applications, particularly in flexible manufacturing systems, there is a high level of uncertainty. A type-2 fuzzy logic system (T2FS) has several parameters and an enhanced ability to handle high levels of uncertainty. This article proposes
Jun-qing Li +3 more
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A Deep Reinforcement Learning Based Solution for Flexible Job Shop Scheduling Problem
International Journal of Simulation Modelling, 2021 Flexible job shop Scheduling problem (FJSP) is a classic problem in combinatorial optimization and a very common form of organization in a real production environment.
B. Han, J. Yang
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Job shop scheduling with beam search [PDF]
European Journal of Operational Research, 1999 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Sabuncuoglu I., Bayiz, M.
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Job Shop Scheduling by Simulated Annealing [PDF]
Operations Research, 1992 We describe an approximation algorithm for the problem of finding the minimum makespan in a job shop. The algorithm is based on simulated annealing, a generalization of the well known iterative improvement approach to combinatorial optimization problems.
Jan Karel Lenstra +2 more
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