Multi-objective sequence dependent setup times permutation flowshop: A new algorithm and a comprehensive study

► We study the multi-objective PFSP with setup times problem. ► Review state of the art on the problem and propose a new benchmark and new algorithm. ► Obtained state of the art results for the proposed benchmark. The permutation flowshop scheduling problem has been thoroughly studied in recent deca...

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Bibliographic Details
Published in:European journal of operational research Vol. 227; no. 2; pp. 301 - 313
Main Authors: Ciavotta, Michele, Minella, Gerardo, Ruiz, Rubén
Format: Journal Article
Language:English
Published: Amsterdam Elsevier B.V 01.06.2013
Elsevier
Elsevier Sequoia S.A
Subjects:
Iterated greedy
Iterative methods
Job shops
Mathematical problems
Multi-objective
Operations research
Pareto optimum
Permutation flowshop
Production scheduling
Scheduling
Scheduling algorithms
Sequence dependent setup times
Studies
Sequence dependent setup times
Scheduling
Permutation flowshop
Multi-objective
Iterated greedy
ISSN:0377-2217, 1872-6860
Online Access:Get full text
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Summary:► We study the multi-objective PFSP with setup times problem. ► Review state of the art on the problem and propose a new benchmark and new algorithm. ► Obtained state of the art results for the proposed benchmark. The permutation flowshop scheduling problem has been thoroughly studied in recent decades, both from single objective as well as from multi-objective perspectives. To the best of our knowledge, little has been done regarding the multi-objective flowshop with Pareto approach when sequence dependent setup times are considered. As setup times and multi-criteria problems are important in industry, we must focus on this area. We propose a simple, yet powerful algorithm for the sequence dependent setup times flowshop problem with several criteria. The presented method is referred to as Restarted Iterated Pareto Greedy or RIPG and is compared against the best performing approaches from the relevant literature. Comprehensive computational and statistical analyses are carried out in order to demonstrate that the proposed RIPG method clearly outperforms all other algorithms and, as a consequence, it is a state-of-art method for this important and practical scheduling problem.
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ISSN:0377-2217
1872-6860
DOI:10.1016/j.ejor.2012.12.031