The constrained permutation flowshop problem: An effective two-stage iterated greedy algorithm to minimize weighted tardiness

•Addressing a novel problem relevant to practice yet unexplored.•Presenting acceleration mechanisms to improve algorithm efficiency.•Proposing an effective Two-Stage Iterated Greedy algorithm.•Proposing three Knowledge-Based repair strategies to handle infeasible solutions.•Presenting three local se...

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Vydáno v:Swarm and evolutionary computation Ročník 91; s. 101696
Hlavní autoři: Li, Qiu-Ying, Pan, Quan-Ke, Gao, Liang, Sang, Hong-Yan, Zhang, Xian-Xia, Li, Wei-Min
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier B.V 01.12.2024
Témata:
Due date
Iterated greedy
Permutation flowshop
Scheduling
Total weighted tardiness
Scheduling
Permutation flowshop
Iterated greedy
Total weighted tardiness
Due date
ISSN:2210-6502
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Shrnutí:•Addressing a novel problem relevant to practice yet unexplored.•Presenting acceleration mechanisms to improve algorithm efficiency.•Proposing an effective Two-Stage Iterated Greedy algorithm.•Proposing three Knowledge-Based repair strategies to handle infeasible solutions.•Presenting three local search methods with problem-specific perturbation operators. In the domain of just-in-time permutation flowshop scheduling, most studies typically assume that all jobs either have their own soft due date or none of them do. However, in practice, scheduling a combination of hard and soft due date jobs, particularly with the context of emergency order insertion, remains a significant research topic. This paper addresses a constrained permutation flowshop scheduling problem with a mix of hard and soft due date jobs under total weighted tardiness criterion (CPFSP-TWT). We establish a mathematical model and propose an effective Two-Stage Iterated Greedy (ETSIG) algorithm tailored to the problem's characteristics, incorporating a two-stage constructive heuristic to generate a high-quality initial solution. We introduce problem-specific acceleration mechanisms based on position-bound considerations to enhance operational efficiency. We propose three knowledge-based repair strategies for handling infeasible solutions, along with a dynamic self-adjustment mechanism. Additionally, three efficient local search procedures integrate several specific perturbation operators to balance algorithmic exploitation and exploration abilities. Experimental evaluations affirm ETSIG's superiority over five state-of-the-art metaheuristics from closely related literature, establishing its efficacy in addressing CPFSP-TWT.
ISSN:2210-6502
DOI:10.1016/j.swevo.2024.101696