An efficient iterated greedy algorithm for a multi-objective no-wait flow shop problem with sequence dependent setup times

In this article, we address the m -machine no-wait flow shop scheduling problem with sequence dependent setup times. The objective is to minimize total tardiness subject to an upper bound on makespan. Although these constraints and performance measures have all been extensively studied independently...

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Vydané v:4OR Ročník 22; číslo 1; s. 31 - 45
Hlavní autori: de Almeida, Fernando Siqueira, Nagano, Marcelo Seido
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2024
Springer Nature B.V
Predmet:
Business and Management
Greedy algorithms
Industrial and Production Engineering
Job shop scheduling
Multiple criterion
Operations research
Operations Research/Decision Theory
Optimization
Research Paper
Setup times
Upper bounds
No-wait
68T20
Iterated greedy
Flow shop
Makespan
90C59
Sequence-dependent setup
Total tardiness
ISSN:1619-4500, 1614-2411
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Shrnutí:In this article, we address the m -machine no-wait flow shop scheduling problem with sequence dependent setup times. The objective is to minimize total tardiness subject to an upper bound on makespan. Although these constraints and performance measures have all been extensively studied independently, they have never been considered together in this problem before. So, this multi-criteria approach provides more realistic solutions for complex scenarios. To solve the problem, we developed a new heuristic called I G A . The proposed method repeatedly performs a process of destruction and construction of an existing solution in order to improve it. The novelty of this method includes a mechanism capable of adapting the destruction intensity according to the instance size and the number of iterations, calibrating the algorithm during the search. Computational experiments indicate that I G A outperforms the best literature method for similar applications in overall solution quality by about 35%. Therefore, I G A is recommended to solve the problem.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1619-4500
1614-2411
DOI:10.1007/s10288-023-00535-7