Journal Article10.1016/j.eswa.2025.130247
An adaptive multi-population algorithm with variable-speed mechanism for multi-objective hybrid lot-streaming flow shop scheduling problem
Fuqing Zhao,Jianlin Zhang,Tian-Peng Xu +2 more
About: This article is published in Expert systems with applications. The article was published on 05 Nov 2025.
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References
The hybrid flow shop scheduling problem
TL;DR: A literature review on exact, heuristic and metaheuristic methods that have been proposed for the solution of the hybrid flow shop problem is presented.
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A review of energy-efficient scheduling in intelligent production systems
TL;DR: This paper aims to provide a comprehensive literature review of production scheduling for intelligent manufacturing systems with the energy-related constraints and objectives, and to give useful insight into future research, especially intelligent strategies for solving theEnergy-efficient scheduling problems.
Green scheduling of distributed two-stage reentrant hybrid flow shop considering distributed energy resources and energy storage system
Jun Dong,Chunming Ye +1 more
TL;DR: Wang et al. as mentioned in this paper established a distributed two-stage reentrant hybrid flow shop bi-level scheduling model, which takes makespan, total carbon emissions and total energy consumption costs as the optimization objectives.
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An automatic multi-objective evolutionary algorithm for the hybrid flowshop scheduling problem with consistent sublots
Schwarz, Silvan
- 01 Feb 2022
TL;DR: In this article , a multi-objective hybrid flow shop scheduling problem with consistent sublots is studied, aiming to simultaneously optimize two conflicting objectives: the makespan and total number of subsets.
53
Improved Meta-Heuristics for Solving Distributed Lot-Streaming Permutation Flow Shop Scheduling Problems
TL;DR: In this paper , a distributed lot-streaming permutation flow shop scheduling problem with makespan constraints is addressed. And five meta-heuristics are executed to solve it, including particle swarm optimization, genetic algorithm, harmony search, artificial bee colony, and Jaya algorithm.
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