Multi-Objective Production Rescheduling: A Systematic Literature Review DOI Creative Commons
Sofia Holguin Jimenez, Wajdi Trabelsi,

Christophe Sauvey

и другие.

Mathematics, Год журнала: 2024, Номер 12(20), С. 3176 - 3176

Опубликована: Окт. 11, 2024

Production rescheduling involves re-optimizing production schedules in response to disruptions that render the initial schedule inefficient or unfeasible. This process requires simultaneous consideration of multiple objectives develop new are both efficient and stable. However, existing review papers have paid limited attention multi-objective optimization techniques employed this context. To address gap, paper presents a systematic literature on rescheduling, examining diverse shop-floor environments. Adhering PRISMA guidelines, total 291 were identified. From pool, studies meeting inclusion criteria selected analyzed provide comprehensive overview problems tackled, dynamic events managed, considered, approaches discussed literature. highlights primary methods used relation strategies disruptive studied. Findings reveal growing interest research area, with “a priori” posteriori” being most commonly implemented notable rise use latter. Hybridized algorithms shown superior performance compared standalone by leveraging combined strengths mitigating individual weaknesses. Additionally, “interactive” “Pareto pruning” methods, as well human factors flexible systems, remain under-explored.

Язык: Английский

A DQL-NSGA-III algorithm for solving the flexible job shop dynamic scheduling problem DOI
Hongtao Tang, Xiao Yu,

Wei Zhang

и другие.

Expert Systems with Applications, Год журнала: 2023, Номер 237, С. 121723 - 121723

Опубликована: Сен. 22, 2023

Язык: Английский

Процитировано

58

A Learning-Driven Multi-Objective cooperative artificial bee colony algorithm for distributed flexible job shop scheduling problems with preventive maintenance and transportation operations DOI

Zhengpei Zhang,

Yaping Fu, Kaizhou Gao

и другие.

Computers & Industrial Engineering, Год журнала: 2024, Номер 196, С. 110484 - 110484

Опубликована: Авг. 18, 2024

Язык: Английский

Процитировано

29

Modeling and optimization algorithm for energy-efficient distributed assembly hybrid flowshop scheduling problem considering worker resources DOI
Fei Yu, Chao Lu, Lvjiang Yin

и другие.

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

Опубликована: Май 3, 2024

Язык: Английский

Процитировано

22

A Q-Learning based NSGA-II for dynamic flexible job shop scheduling with limited transportation resources DOI

Rensheng Chen,

Bin Wu, Hua Wang

и другие.

Swarm and Evolutionary Computation, Год журнала: 2024, Номер 90, С. 101658 - 101658

Опубликована: Июль 18, 2024

Язык: Английский

Процитировано

15

A reinforcement learning enhanced memetic algorithm for multi-objective flexible job shop scheduling toward Industry 5.0 DOI
Xiao Chang, Xiaoliang Jia, Jiahao Ren

и другие.

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

Процитировано

14

A Pareto-optimality based black widow spider algorithm for energy efficient flexible job shop scheduling problem considering new job insertion DOI
Kashif Akram, M. Usman Maqbool Bhutta, Shahid Ikramullah Butt

и другие.

Applied Soft Computing, Год журнала: 2024, Номер 164, С. 111937 - 111937

Опубликована: Июль 6, 2024

Язык: Английский

Процитировано

10

An Inverse Reinforcement Learning Algorithm with Population Evolution Mechanism for The Multi-objective Flexible Job-shop Scheduling Problem under Time-of-use Electricity Tariffs DOI
Fuqing Zhao, Weiyuan Wang, Ningning Zhu

и другие.

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

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

2

Multi-objective fitness landscape-based estimation of distribution algorithm for distributed heterogeneous flexible job shop scheduling problem DOI
Fuqing Zhao, Mengjie Li, Ningning Zhu

и другие.

Applied Soft Computing, Год журнала: 2025, Номер unknown, С. 112780 - 112780

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

2

Learning-driven memetic algorithm for solving integrated distributed production and transportation scheduling problem DOI
Shicun Zhao, Hong Zhou

Swarm and Evolutionary Computation, Год журнала: 2025, Номер 96, С. 101945 - 101945

Опубликована: Май 4, 2025

Язык: Английский

Процитировано

1

Scheduling analysis of automotive glass manufacturing systems subject to sequence-independent setup time, no-idle machines, and permissive maximum total tardiness constraint DOI
YunFang He, Yan Qiao, Naiqi Wu

и другие.

Engineering Applications of Artificial Intelligence, Год журнала: 2024, Номер 133, С. 108299 - 108299

Опубликована: Март 21, 2024

Язык: Английский

Процитировано

6