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Supply chain optimisation using evolutionary algorithms.

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Title: Supply chain optimisation using evolutionary algorithms.
Authors: Falcone, Marco Aurelio1, Lopes, Heitor Silverio2, Coelho, Leandro Dos Santos3
Source: International Journal of Computer Applications in Technology. 2008, Vol. 31 Issue 3/4, p158-167. 10p.
Subjects: Evaluation, Application logging (Computer science), Theory-practice relationship, Genetic algorithms, Numerical solutions to evolution equations, Evolutionary computation, Physical distribution of goods, Combinatorial optimization, Business logistics
Abstract: This paper describes the application of Evolutionary Algorithms (EAs) to the optimisation of a simplified supply chain in an integrated production-inventory-distribution system. The performance of four EAs (Genetic Algorithm (GA), Evolutionary Programming (EP), Evolution Strategies (ES) and Differential Evolution (DE)) was evaluated with numerical simulations. Results were also compared with other similar approaches in the literature. DE was the algorithm that led to better results, outperforming previously published solutions. The robustness of EAs in general, and the efficiency of DE, in particular, suggest their great utility for the supply chain optimisation problem, as well as for other logistics-related problems. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Computer Applications in Technology is the property of Inderscience Enterprises 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.)
Database: Engineering Source
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Header DbId: egs
DbLabel: Engineering Source
An: 32021042
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
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  Data: Supply chain optimisation using evolutionary algorithms.
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Computer+Applications+in+Technology%22">International Journal of Computer Applications in Technology</searchLink>. 2008, Vol. 31 Issue 3/4, p158-167. 10p.
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  Data: <searchLink fieldCode="DE" term="%22Evaluation%22">Evaluation</searchLink><br /><searchLink fieldCode="DE" term="%22Application+logging+%28Computer+science%29%22">Application logging (Computer science)</searchLink><br /><searchLink fieldCode="DE" term="%22Theory-practice+relationship%22">Theory-practice relationship</searchLink><br /><searchLink fieldCode="DE" term="%22Genetic+algorithms%22">Genetic algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Numerical+solutions+to+evolution+equations%22">Numerical solutions to evolution equations</searchLink><br /><searchLink fieldCode="DE" term="%22Evolutionary+computation%22">Evolutionary computation</searchLink><br /><searchLink fieldCode="DE" term="%22Physical+distribution+of+goods%22">Physical distribution of goods</searchLink><br /><searchLink fieldCode="DE" term="%22Combinatorial+optimization%22">Combinatorial optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Business+logistics%22">Business logistics</searchLink>
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  Data: This paper describes the application of Evolutionary Algorithms (EAs) to the optimisation of a simplified supply chain in an integrated production-inventory-distribution system. The performance of four EAs (Genetic Algorithm (GA), Evolutionary Programming (EP), Evolution Strategies (ES) and Differential Evolution (DE)) was evaluated with numerical simulations. Results were also compared with other similar approaches in the literature. DE was the algorithm that led to better results, outperforming previously published solutions. The robustness of EAs in general, and the efficiency of DE, in particular, suggest their great utility for the supply chain optimisation problem, as well as for other logistics-related problems. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Computer Applications in Technology is the property of Inderscience Enterprises 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.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=32021042
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1504/IJCAT.2008.018154
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 10
        StartPage: 158
    Subjects:
      – SubjectFull: Evaluation
        Type: general
      – SubjectFull: Application logging (Computer science)
        Type: general
      – SubjectFull: Theory-practice relationship
        Type: general
      – SubjectFull: Genetic algorithms
        Type: general
      – SubjectFull: Numerical solutions to evolution equations
        Type: general
      – SubjectFull: Evolutionary computation
        Type: general
      – SubjectFull: Physical distribution of goods
        Type: general
      – SubjectFull: Combinatorial optimization
        Type: general
      – SubjectFull: Business logistics
        Type: general
    Titles:
      – TitleFull: Supply chain optimisation using evolutionary algorithms.
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            NameFull: Falcone, Marco Aurelio
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            NameFull: Lopes, Heitor Silverio
      – PersonEntity:
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            NameFull: Coelho, Leandro Dos Santos
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            – D: 01
              M: 03
              Text: 2008
              Type: published
              Y: 2008
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              Value: 31
            – Type: issue
              Value: 3/4
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            – TitleFull: International Journal of Computer Applications in Technology
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