Mathematical model and knowledge-based iterated greedy algorithm for distributed assembly hybrid flow shop scheduling problem with dual-resource constraints

Expert Systems with Applications, Год журнала: 2023, Номер 239, С. 122434 - 122434

Опубликована: Ноя. 4, 2023

Язык: Английский

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Modeling and optimization algorithm for energy-efficient distributed assembly hybrid flowshop scheduling problem considering worker resources

Journal of Industrial Information Integration, Год журнала: 2024, Номер 40, С. 100620 - 100620

Опубликована: Май 3, 2024

Язык: Английский

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A disjunctive graph-based metaheuristic for flexible job-shop scheduling problems considering fixture shortages in customized manufacturing systems

Robotics and Computer-Integrated Manufacturing, Год журнала: 2025, Номер 95, С. 102981 - 102981

Опубликована: Фев. 20, 2025

Язык: Английский

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Multi-objective optimization of energy-efficient remanufacturing system scheduling problem with lot-streaming production mode

Expert Systems with Applications, Год журнала: 2023, Номер 237, С. 121309 - 121309

Опубликована: Сен. 5, 2023

Язык: Английский

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Multi-objective green scheduling of integrated flexible job shop and automated guided vehicles

Engineering Applications of Artificial Intelligence, Год журнала: 2023, Номер 126, С. 106864 - 106864

Опубликована: Авг. 9, 2023

Язык: Английский

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A reinforcement learning enhanced memetic algorithm for multi-objective flexible job shop scheduling toward Industry 5.0

International Journal of Production Research, Год журнала: 2024, Номер unknown, С. 1 - 29

Опубликована: Май 30, 2024

Flexible job shop scheduling problem (FJSP) with worker flexibility has gained significant attention in the upcoming Industry 5.0 era because of its computational complexity and importance production processes. It is normally assumed that each machine typically operated by one at any time; therefore, shop-floor managers need to decide on most efficient assignments for machines workers. However, processing time variable uncertain due fluctuating environment caused unsteady operating conditions learning effect Meanwhile, they also balance workload while meeting efficiency. Thus a dual resource-constrained FJSP worker's fuzzy (F-DRCFJSP-WL) investigated simultaneously minimise makespan, total workloads maximum workload. Subsequently, reinforcement enhanced multi-objective memetic algorithm based decomposition (RL-MOMA/D) proposed solving F-DRCFJSP-WL. For RL-MOMA/D, Q-learning incorporated into perform neighbourhood search further strengthen exploitation capability algorithm. Finally, comprehensive experiments extensive test instances case study aircraft overhaul are conducted demonstrate effectiveness superiority method.

Язык: Английский

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Matheuristic and learning-oriented multi-objective artificial bee colony algorithm for energy-aware flexible assembly job shop scheduling problem

Engineering Applications of Artificial Intelligence, Год журнала: 2024, Номер 133, С. 108634 - 108634

Опубликована: Май 20, 2024

Язык: Английский

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An Inverse Reinforcement Learning Algorithm with Population Evolution Mechanism for The Multi-objective Flexible Job-shop Scheduling Problem under Time-of-use Electricity Tariffs

Applied Soft Computing, Год журнала: 2025, Номер unknown, С. 112764 - 112764

Опубликована: Янв. 1, 2025

Язык: Английский

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Tackling dual-resource flexible job shop scheduling problem in the production line reconfiguration scenario: An efficient meta-heuristic with critical path-based neighborhood search

Advanced Engineering Informatics, Год журнала: 2025, Номер 65, С. 103282 - 103282

Опубликована: Апрель 3, 2025

Язык: Английский

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An effective memetic algorithm for distributed flexible job shop scheduling problem considering integrated sequencing flexibility

Expert Systems with Applications, Год журнала: 2023, Номер 242, С. 122734 - 122734

Опубликована: Ноя. 30, 2023

Язык: Английский

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