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Fuzzy bi-objective formulation for a parallel machine scheduling problem with machine eligibility restrictions and sequence-dependent setup times.

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Title: Fuzzy bi-objective formulation for a parallel machine scheduling problem with machine eligibility restrictions and sequence-dependent setup times.
Authors: Naderi-Beni, Mahdi1 (AUTHOR), Ghobadian, Ehsan1 (AUTHOR), Ebrahimnejad, Sadoullah2 (AUTHOR) ibrahimnejad@kiau.ac.ir, Tavakkoli-Moghaddam, Reza3 (AUTHOR)
Source: International Journal of Production Research. Oct2014, Vol. 52 Issue 19, p5799-5822. 24p. 2 Diagrams, 18 Charts.
Subjects: Production scheduling, Parallel scheduling (Computer scheduling), Fuzzy algorithms, Heuristic algorithms, Mathematical optimization, Load balancing (Computer networks)
Abstract: In this paper, a fuzzy bi-objective mixed-integer linear programming (FBOMILP) model is presented. FBOMILP encompasses the minimisation workload imbalance and total tardiness simultaneously as a bi-objective formulation for an unrelated parallel machine scheduling problem. To make the proposed model more practical, sequence-dependent setup times, machine eligibility restrictions and release dates are also considered. Moreover, the inherent uncertainty of processing times, release dates, setup times and due dates are taken into account and modelled by fuzzy numbers. In order to solve the model for small-scale problems, a two-stage fuzzy approach is proposed. Nevertheless, since the problem belongs to the class of NP-hard problems, the proposed model is solved by two meta-heuristic algorithms, namely fuzzy multi-objective particle swarm optimisation (FMOPSO) and fuzzy non-dominated sorting genetic algorithm (FNSGA-II) for solving large-scale instances. Subsequently, through setting up various numerical examples, the performances of the two mentioned algorithms are compared. Whenα = 0.5 (αis a level of risk-taking and when it increases the decision-maker’s risk-taking decreases), FNSGA-II is fairly more effective than FMOPSO and has better performance especially in solving large-sized problems. However, whenαrises, it can be stated that FMOPSO moderately becomes more appropriate. Finally, directions for future studies are suggested and conclusion remarks are drawn. [ABSTRACT FROM PUBLISHER]
Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Label: Title
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  Data: Fuzzy bi-objective formulation for a parallel machine scheduling problem with machine eligibility restrictions and sequence-dependent setup times.
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  Data: <searchLink fieldCode="AR" term="%22Naderi-Beni%2C+Mahdi%22">Naderi-Beni, Mahdi</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ghobadian%2C+Ehsan%22">Ghobadian, Ehsan</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ebrahimnejad%2C+Sadoullah%22">Ebrahimnejad, Sadoullah</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> ibrahimnejad@kiau.ac.ir</i><br /><searchLink fieldCode="AR" term="%22Tavakkoli-Moghaddam%2C+Reza%22">Tavakkoli-Moghaddam, Reza</searchLink><relatesTo>3</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Production+Research%22">International Journal of Production Research</searchLink>. Oct2014, Vol. 52 Issue 19, p5799-5822. 24p. 2 Diagrams, 18 Charts.
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  Data: <searchLink fieldCode="DE" term="%22Production+scheduling%22">Production scheduling</searchLink><br /><searchLink fieldCode="DE" term="%22Parallel+scheduling+%28Computer+scheduling%29%22">Parallel scheduling (Computer scheduling)</searchLink><br /><searchLink fieldCode="DE" term="%22Fuzzy+algorithms%22">Fuzzy algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Heuristic+algorithms%22">Heuristic algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+optimization%22">Mathematical optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Load+balancing+%28Computer+networks%29%22">Load balancing (Computer networks)</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: In this paper, a fuzzy bi-objective mixed-integer linear programming (FBOMILP) model is presented. FBOMILP encompasses the minimisation workload imbalance and total tardiness simultaneously as a bi-objective formulation for an unrelated parallel machine scheduling problem. To make the proposed model more practical, sequence-dependent setup times, machine eligibility restrictions and release dates are also considered. Moreover, the inherent uncertainty of processing times, release dates, setup times and due dates are taken into account and modelled by fuzzy numbers. In order to solve the model for small-scale problems, a two-stage fuzzy approach is proposed. Nevertheless, since the problem belongs to the class of NP-hard problems, the proposed model is solved by two meta-heuristic algorithms, namely fuzzy multi-objective particle swarm optimisation (FMOPSO) and fuzzy non-dominated sorting genetic algorithm (FNSGA-II) for solving large-scale instances. Subsequently, through setting up various numerical examples, the performances of the two mentioned algorithms are compared. Whenα = 0.5 (αis a level of risk-taking and when it increases the decision-maker’s risk-taking decreases), FNSGA-II is fairly more effective than FMOPSO and has better performance especially in solving large-sized problems. However, whenαrises, it can be stated that FMOPSO moderately becomes more appropriate. Finally, directions for future studies are suggested and conclusion remarks are drawn. [ABSTRACT FROM PUBLISHER]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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        Value: 10.1080/00207543.2014.916430
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      – Code: eng
        Text: English
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        PageCount: 24
        StartPage: 5799
    Subjects:
      – SubjectFull: Production scheduling
        Type: general
      – SubjectFull: Parallel scheduling (Computer scheduling)
        Type: general
      – SubjectFull: Fuzzy algorithms
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      – SubjectFull: Heuristic algorithms
        Type: general
      – SubjectFull: Mathematical optimization
        Type: general
      – SubjectFull: Load balancing (Computer networks)
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      – TitleFull: Fuzzy bi-objective formulation for a parallel machine scheduling problem with machine eligibility restrictions and sequence-dependent setup times.
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            NameFull: Naderi-Beni, Mahdi
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            NameFull: Ghobadian, Ehsan
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            NameFull: Ebrahimnejad, Sadoullah
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            NameFull: Tavakkoli-Moghaddam, Reza
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          Dates:
            – D: 01
              M: 10
              Text: Oct2014
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