Robust scheduling for multi-objective flexible job-shop problems with random machine breakdowns

This study addresses robust scheduling for a flexible job-shop scheduling problem with random machine breakdowns. Two objectives – makespan and robustness – are simultaneously considered. Robustness is indicated by the expected value of the relative difference between the deterministic and actual ma...

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Published inInternational journal of production economics Vol. 141; no. 1; pp. 112 - 126
Main Authors Xiong, Jian, Xing, Li-ning, Chen, Ying-wu
Format Journal Article
LanguageEnglish
Published Amsterdam Elsevier B.V 01.01.2013
Elsevier
Elsevier Sequoia S.A
Subjects
Online AccessGet full text
ISSN0925-5273
1873-7579
DOI10.1016/j.ijpe.2012.04.015

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Abstract This study addresses robust scheduling for a flexible job-shop scheduling problem with random machine breakdowns. Two objectives – makespan and robustness – are simultaneously considered. Robustness is indicated by the expected value of the relative difference between the deterministic and actual makespan. Utilizing the available information about machine breakdowns, two surrogate measures for robustness are developed. Specifically, the first suggested surrogate measure considers the probability of machine breakdowns, while the second surrogate measure considers the location of float times and machine breakdowns. To address this problem, a multi-objective evolutionary algorithm is presented in this paper. The experimental results indicate that, compared with several other existing surrogate measures, the first suggested surrogate measure performs better for small cases, while the second surrogate measure performs better for both small and relatively large cases.
AbstractList This study addresses robust scheduling for a flexible job-shop scheduling problem with random machine breakdowns. Two objectives – makespan and robustness – are simultaneously considered. Robustness is indicated by the expected value of the relative difference between the deterministic and actual makespan. Utilizing the available information about machine breakdowns, two surrogate measures for robustness are developed. Specifically, the first suggested surrogate measure considers the probability of machine breakdowns, while the second surrogate measure considers the location of float times and machine breakdowns. To address this problem, a multi-objective evolutionary algorithm is presented in this paper. The experimental results indicate that, compared with several other existing surrogate measures, the first suggested surrogate measure performs better for small cases, while the second surrogate measure performs better for both small and relatively large cases.
This study addresses robust scheduling for a flexible job-shop scheduling problem with random machine breakdowns. Two objectives -- makespan and robustness -- are simultaneously considered. Robustness is indicated by the expected value of the relative difference between the deterministic and actual makespan. Utilizing the available information about machine breakdowns, two surrogate measures for robustness are developed. Specifically, the first suggested surrogate measure considers the probability of machine breakdowns, while the second surrogate measure considers the location of float times and machine breakdowns. To address this problem, a multi-objective evolutionary algorithm is presented in this paper. The experimental results indicate that, compared with several other existing surrogate measures, the first suggested surrogate measure performs better for small cases, while the second surrogate measure performs better for both small and relatively large cases. [PUBLICATION ABSTRACT]
This study addresses robust scheduling for a flexible job-shop scheduling problem with random machine breakdowns. Two objectives a makespan and robustness a are simultaneously considered. Robustness is indicated by the expected value of the relative difference between the deterministic and actual makespan. Utilizing the available information about machine breakdowns, two surrogate measures for robustness are developed. Specifically, the first suggested surrogate measure considers the probability of machine breakdowns, while the second surrogate measure considers the location of float times and machine breakdowns. To address this problem, a multi-objective evolutionary algorithm is presented in this paper. The experimental results indicate that, compared with several other existing surrogate measures, the first suggested surrogate measure performs better for small cases, while the second surrogate measure performs better for both small and relatively large cases.
Author Xiong, Jian
Chen, Ying-wu
Xing, Li-ning
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Keywords Flexible job-shop schedule problem
Robust scheduling
Machine breakdowns
Multi-objective evolutionary algorithm
Surrogate measure
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Snippet This study addresses robust scheduling for a flexible job-shop scheduling problem with random machine breakdowns. Two objectives – makespan and robustness –...
This study addresses robust scheduling for a flexible job-shop scheduling problem with random machine breakdowns. Two objectives -- makespan and robustness --...
This study addresses robust scheduling for a flexible job-shop scheduling problem with random machine breakdowns. Two objectives a makespan and robustness a...
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SubjectTerms Breakdown
Breakdowns
Economics
Evolutionary algorithms
Expected values
Flexible job-shop schedule problem
Floats
Genetic algorithms
Job shops
Machine breakdowns
Multi-objective evolutionary algorithm
Operations research
Position (location)
Production scheduling
Robust scheduling
Robustness
Scheduling
Studies
Surrogate measure
Title Robust scheduling for multi-objective flexible job-shop problems with random machine breakdowns
URI https://dx.doi.org/10.1016/j.ijpe.2012.04.015
http://www.econis.eu/PPNSET?PPN=734422350
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