Swarm and Evolutionary Computation, Journal Year: 2020, Volume and Issue: 58, P. 100739 - 100739
Published: July 13, 2020
Language: Английский
International Journal of Production Research, Journal Year: 2022, Volume and Issue: 61(5), P. 1373 - 1393
Published: Jan. 19, 2022
In a complex and dynamic job shop containing logistics factor, schedule needs to be generated rapidly, so the real-time scheduling method is more suitable for such scenario. Such takes advantage of local information within short time due rapid changes under uncertain environment. Therefore, how make use future by prediction while ensuring robustness valuable problem. To solve it, firstly, new model algorithm proposed. There kind release moment task which can give AGVs longest prepare than existing research. Secondly, update mechanism designed increase schedule's robustness. Finally, large-scale simulation experimental platform developed. Dynamic factors include random insertion orders failures equipment. Results show that proposed outperforms research in terms customer satisfaction, equipment utilisation energy consumption. The also acceptable. This paper finds rule with large proportion transportation time, above achieve competitive results.
Language: Английский
Citations
51
Engineering Applications of Artificial Intelligence, Journal Year: 2023, Volume and Issue: 123, P. 106230 - 106230
Published: April 11, 2023
Language: Английский
Citations
30
Robotics and Computer-Integrated Manufacturing, Journal Year: 2020, Volume and Issue: 68, P. 102081 - 102081
Published: Oct. 14, 2020
Language: Английский
Citations
55
Computers & Industrial Engineering, Journal Year: 2022, Volume and Issue: 176, P. 108921 - 108921
Published: Dec. 22, 2022
Language: Английский
Citations
38
International Journal of Production Research, Journal Year: 2022, Volume and Issue: 61(3), P. 1013 - 1038
Published: July 4, 2022
Lot streaming is the most widely used technique to facilitate overlap of successive operations. Considering consistent sublots and machine breakdown, this study investigates multi-objective hybrid flowshop rescheduling problem with (MOHFRP_CS), which aims at optimising total completion time, starting time deviations operations, average adjustment sublot sizes simultaneously. By introducing decomposition strategy effective migrating birds optimisation framework, paper develops a algorithm based on (MMBO/D). In MMBO/D, decomposed into series sub-problems, its solutions are initialised by Glover operator further optimised variable neighbourhood descent strategy. The weights assigned sub-problems adapted dynamically according weight strategy, global update employed solutions. A novel sharing benefiting mechanism proposed implement coevolution among different sub-problems. Competitive mechanisms modified considering similar improve population quality. criterion designed check whether subproblem stuck in local optima. comprehensive computational results demonstrate that MMBO/D outperforms other state-of-the-art evolutionary algorithms (MOEAs) for addressed problem.
Language: Английский
Citations
30
Computers & Operations Research, Journal Year: 2024, Volume and Issue: 164, P. 106563 - 106563
Published: Jan. 28, 2024
Language: Английский
Citations
8
Soft Computing, Journal Year: 2020, Volume and Issue: 24(17), P. 13461 - 13487
Published: Feb. 12, 2020
Language: Английский
Citations
42
Journal of Cleaner Production, Journal Year: 2022, Volume and Issue: 385, P. 135738 - 135738
Published: Dec. 29, 2022
Language: Английский
Citations
23
International Journal of Production Research, Journal Year: 2023, Volume and Issue: 62(13), P. 4793 - 4808
Published: Nov. 9, 2023
Hybrid flow shop scheduling problem (HFSP) with real-life constraints has been extensively considered; however, HFSP batch processing machines (BPM) at a middle stage is seldom investigated. In this study, BPM in hot & cold casting process considered and an adaptive artificial bee colony (AABC) proposed to minimise makespan. To produce high quality solutions, search employed phase step implemented. Adaptive step, which may be onlooker or cooperation empty, decided by evolution threshold. Cooperation performed between the improved solutions of one swarm unimproved another swarm. Six operators are constructed operator adaptively adjusted. A new scout also given. lower bound provided proved. Extensive experiments conducted. The computational results validate that strategies such as effective efficient AABC can obtain better than methods from existing literature on problem.
Language: Английский
Citations
16
ACM Computing Surveys, Journal Year: 2023, Volume and Issue: 55(14s), P. 1 - 36
Published: April 1, 2023
As one of the most complex parts in manufacturing systems, scheduling plays an important role efficient allocation resources to meet individual customization requirements. However, due uncertain disruptions (e.g., task arrival time, service breakdown duration) processes, how respond various dynamics keep process moving forward smoothly and efficiently is becoming a major challenge dynamic scheduling. To solve such problem, wide spectrum artificial intelligence techniques have been developed (1) accurately construct models that can represent both personalized customer needs provider capabilities (2) obtain qualified schedule within limited time. From these two perspectives, this article systemically makes state-of-the-art literature survey on application modeling It first introduces types problems consider service- task-related process, respectively, followed by bibliometric analysis for Next, kinds artificial-intelligence-enabled schedulers solving including directed heuristics autonomous learning methods are reviewed, which strive not only quickly optimized solutions but also effectively achieve adaption dynamics. Finally, further elaborates future opportunities challenges using problems. In summary, aims present thorough organized overview shed light some related research directions worth studying future.
Language: Английский
Citations
13