A single-individual based variable neighborhood search algorithm for the blocking hybrid flow shop group scheduling problem DOI Creative Commons

Zhongyuan Peng,

Haoxiang Qin

Egyptian Informatics Journal, Journal Year: 2024, Volume and Issue: 27, P. 100509 - 100509

Published: July 30, 2024

Language: Английский

Mathematical model and knowledge-based iterated greedy algorithm for distributed assembly hybrid flow shop scheduling problem with dual-resource constraints DOI
Fei Yu, Chao Lu, Jiajun Zhou

et al.

Expert Systems with Applications, Journal Year: 2023, Volume and Issue: 239, P. 122434 - 122434

Published: Nov. 4, 2023

Language: Английский

Citations

43
A distributed permutation flow-shop considering sustainability criteria and real-time scheduling DOI Creative Commons
Amir M. Fathollahi‐Fard, L. A. Woodward,

Ouassima Akhrif

et al.

Journal of Industrial Information Integration, Journal Year: 2024, Volume and Issue: 39, P. 100598 - 100598

Published: March 12, 2024

Recent advancements in production scheduling have arisen response to the need for adaptation dynamic environments. This paper addresses challenge of real-time within context sustainable production. We redefine distributed permutation flow-shop problem using an online mixed-integer programming model. The proposed model prioritizes minimizing makespan while simultaneously constraining energy consumption, reducing number lost working days and increasing job opportunities permissible limits. Our approach considers machines operating different modes, ranging from manual automatic, employs two strategies: predictive-reactive proactive-reactive scheduling. evaluate rescheduling policies: continuous event-driven. To demonstrate model's applicability, we present a case study auto workpiece manage complexity through various reformulations heuristics, such as Lagrangian relaxation Benders decomposition initial optimization well four problem-specific heuristics considerations. For solving large-scale instances, employ simulated annealing tabu search metaheuristic algorithms. findings underscore benefits strategy efficiency event-driven policy. By addressing challenges integrating sustainability criteria, this contributes valuable insights into

Language: Английский

Citations

26
MRLM: A meta-reinforcement learning-based metaheuristic for hybrid flow-shop scheduling problem with learning and forgetting effects DOI
Zeyu Zhang, Zhongshi Shao, Weishi Shao

et al.

Swarm and Evolutionary Computation, Journal Year: 2024, Volume and Issue: 85, P. 101479 - 101479

Published: Jan. 10, 2024

Language: Английский

Citations

20
Review on ensemble meta-heuristics and reinforcement learning for manufacturing scheduling problems DOI
Yaping Fu, Yifeng Wang, Kaizhou Gao

et al.

Computers & Electrical Engineering, Journal Year: 2024, Volume and Issue: 120, P. 109780 - 109780

Published: Oct. 18, 2024

Language: Английский

Citations

15
A feedback learning-based selection hyper-heuristic for distributed heterogeneous hybrid blocking flow-shop scheduling problem with flexible assembly and setup time DOI
Zhongshi Shao, Weishi Shao,

Jianrui Chen

et al.

Engineering Applications of Artificial Intelligence, Journal Year: 2024, Volume and Issue: 131, P. 107818 - 107818

Published: Jan. 9, 2024

Language: Английский

Citations

11
Enhancing distributed blocking flowshop group scheduling: Theoretical insight and application of an iterated greedy algorithm with idle time insertion and rapid evaluation mechanisms DOI

Yizheng Wang,

Yuting Wang, Yuyan Han

et al.

Expert Systems with Applications, Journal Year: 2025, Volume and Issue: unknown, P. 126600 - 126600

Published: Jan. 1, 2025

Language: Английский

Citations

1
A variable-representation discrete artificial bee colony algorithm for a constrained hybrid flow shop DOI
Zecheng Wang, Quan-Ke Pan, Liang Gao

et al.

Expert Systems with Applications, Journal Year: 2024, Volume and Issue: 254, P. 124349 - 124349

Published: May 28, 2024

Language: Английский

Citations

8
A multidimensional probabilistic model based evolutionary algorithm for the energy-efficient distributed flexible job-shop scheduling problem DOI

Zi-Qi Zhang,

Ying Li, Bin Qian

et al.

Engineering Applications of Artificial Intelligence, Journal Year: 2024, Volume and Issue: 135, P. 108841 - 108841

Published: June 18, 2024

Language: Английский

Citations

6
Effective metaheuristic and rescheduling strategies for the multi-AGV scheduling problem with sudden failure DOI
Xue Wang, Wenqiang Zou, Leilei Meng

et al.

Expert Systems with Applications, Journal Year: 2024, Volume and Issue: 250, P. 123473 - 123473

Published: Feb. 27, 2024

Language: Английский

Citations

5
A Q-learning grey wolf optimizer for a distributed hybrid flowshop rescheduling problem with urgent job insertion DOI
Shuilin Chen, Jianguo Zheng

Journal of Applied Mathematics and Computing, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 17, 2025

Language: Английский

Citations

0