eBook
View in EDS

Handbook of AI-based Metaheuristics

Bibliographic Details
Title: Handbook of AI-based Metaheuristics
Description: At the heart of the optimization domain are mathematical modeling of the problem and the solution methodologies. The problems are becoming larger and with growing complexity. Such problems are becoming cumbersome when handled by traditional optimization methods. This has motivated researchers to resort to artificial intelligence (AI)-based, nature-inspired solution methodologies or algorithms.The Handbook of AI-based Metaheuristics provides a wide-ranging reference to the theoretical and mathematical formulations of metaheuristics, including bio-inspired, swarm-based, socio-cultural, and physics-based methods or algorithms; their testing and validation, along with detailed illustrative solutions and applications; and newly devised metaheuristic algorithms.This will be a valuable reference for researchers in industry and academia, as well as for all Master's and PhD students working in the metaheuristics and applications domains.
Authors: Anand J. Kulkarni, Patrick Siarry
Resource Type: eBook.
Subjects: Artificial intelligence, Systems engineering--Data processing, Metaheuristics, Mathematical optimization, Heuristic algorithms
Categories: MATHEMATICS / Optimization, COMPUTERS / Programming / Algorithms, TECHNOLOGY & ENGINEERING / Operations Research
Database: eBook Index
FullText Text:
  Availability: 0
Header DbId: edsebk
DbLabel: eBook Index
An: 2892272
RelevancyScore: 956
AccessLevel: 6
PubType: eBook
PubTypeId: ebook
PreciseRelevancyScore: 955.975708007813
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Handbook of AI-based Metaheuristics
– Name: Abstract
  Label: Description
  Group: Ab
  Data: At the heart of the optimization domain are mathematical modeling of the problem and the solution methodologies. The problems are becoming larger and with growing complexity. Such problems are becoming cumbersome when handled by traditional optimization methods. This has motivated researchers to resort to artificial intelligence (AI)-based, nature-inspired solution methodologies or algorithms.The Handbook of AI-based Metaheuristics provides a wide-ranging reference to the theoretical and mathematical formulations of metaheuristics, including bio-inspired, swarm-based, socio-cultural, and physics-based methods or algorithms; their testing and validation, along with detailed illustrative solutions and applications; and newly devised metaheuristic algorithms.This will be a valuable reference for researchers in industry and academia, as well as for all Master's and PhD students working in the metaheuristics and applications domains.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Anand+J%2E+Kulkarni%22">Anand J. Kulkarni</searchLink><br /><searchLink fieldCode="AR" term="%22Patrick+Siarry%22">Patrick Siarry</searchLink>
– Name: TypePub
  Label: Resource Type
  Group: TypPub
  Data: eBook.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Systems+engineering--Data+processing%22">Systems engineering--Data processing</searchLink><br /><searchLink fieldCode="DE" term="%22Metaheuristics%22">Metaheuristics</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+optimization%22">Mathematical optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Heuristic+algorithms%22">Heuristic algorithms</searchLink>
– Name: SubjectBISAC
  Label: Categories
  Group: Su
  Data: <searchLink fieldCode="ZK" term="%22MATHEMATICS+%2F+Optimization%22">MATHEMATICS / Optimization</searchLink><br /><searchLink fieldCode="ZK" term="%22COMPUTERS+%2F+Programming+%2F+Algorithms%22">COMPUTERS / Programming / Algorithms</searchLink><br /><searchLink fieldCode="ZK" term="%22TECHNOLOGY+%26+ENGINEERING+%2F+Operations+Research%22">TECHNOLOGY & ENGINEERING / Operations Research</searchLink>
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=2892272
RecordInfo BibRecord:
  BibEntity:
    Classifications:
      – Code: 620.0042028563
        Scheme: ddc
        Type: prePub
    Languages:
      – Code: eng
        Text: English
    Subjects:
      – SubjectFull: Artificial intelligence
        Type: general
      – SubjectFull: Systems engineering--Data processing
        Type: general
      – SubjectFull: Metaheuristics
        Type: general
      – SubjectFull: Mathematical optimization
        Type: general
      – SubjectFull: Heuristic algorithms
        Type: general
    Titles:
      – TitleFull: Handbook of AI-based Metaheuristics
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Anand J. Kulkarni
      – PersonEntity:
          Name:
            NameFull: Patrick Siarry
      – PersonEntity:
          Name:
            NameFull: Anand J. Kulkarni
      – PersonEntity:
          Name:
            NameFull: Patrick Siarry
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2021
            – D: 10
              M: 12
              Type: profile
              Y: 2021
          Identifiers:
            – Type: isbn-print
              Value: 9780367753030
            – Type: isbn-print
              Value: 9780367755355
            – Type: isbn-electronic
              Value: 9781000434248
            – Type: isbn-electronic
              Value: 9781000434255
            – Type: isbn-electronic
              Value: 9781003162841
          Titles:
            – TitleFull: Handbook of AI-based Metaheuristics
              Type: main
ResultId 1