A systematic literature review on energy-efficient hybrid flow shop scheduling

Cogent Engineering, Journal Year: 2023, Volume and Issue: 10(1)

Published: May 1, 2023

Scheduling problems should not only focus on minimizing completion time, but other performances, such as energy consumption, are urgent to investigate. Many companies and researchers competing develop various methods solve this problem. One problem that has received much attention lately is the energy-efficient Hybrid Flow Shop Problem (HFSP). The HFSP also popularly called flexible flow shop This research provides a comprehensive review of articles discuss scheduling determine trend gaps for future interests. uses systematic literature method. total reviewed in study 90 from January 2008 - December 2022. classified by year, country, journal/conferences, publisher, objective function, analysis results show continues increase. In addition, multi-objective dominating problems. presents gap directions.

Language: Английский

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A knowledge-driven cooperative scatter search algorithm with reinforcement learning for the distributed blocking flow shop scheduling problem

Expert Systems with Applications, Journal Year: 2023, Volume and Issue: 230, P. 120571 - 120571

Published: June 2, 2023

Language: Английский

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An adaptive artificial bee colony for hybrid flow shop scheduling with batch processing machines in casting process

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

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A Dual-Population Genetic Algorithm with Q-Learning for Multi-Objective Distributed Hybrid Flow Shop Scheduling Problem

Symmetry, Journal Year: 2023, Volume and Issue: 15(4), P. 836 - 836

Published: March 30, 2023

In real-world production processes, the same enterprise often has multiple factories or one factory lines, and objectives need to be considered in process. A dual-population genetic algorithm with Q-learning is proposed minimize maximum completion time number of tardy jobs for distributed hybrid flow shop scheduling problems, which have some symmetries machines. Multiple crossover mutation operators are proposed, only search strategy combination, including operator operator, selected each iteration. population assessment method provided evaluate evolutionary state at initial after Two populations adopt different strategies, best first second under guidance Q-learning. Experimental results show that competitive solving multi-objective problems.

Language: Английский

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An artificial bee colony with diversified operators for energy-efficient hybrid flow shop scheduling with batch processing machines

Engineering Applications of Artificial Intelligence, Journal Year: 2024, Volume and Issue: 136, P. 108930 - 108930

Published: July 29, 2024

Language: Английский

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