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Herausgeber: 
  • Panos M. Pardalos
  • Mauricio G. C. Resende
  • Rafael Martí
  • Handbook of Heuristics 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  August 2018  
    Genre:  Schulbücher 
     
    A / Algorithms / Analysis / Analysis (Mathematics) / Applied mathematics / Calculus & mathematical analysis / Computer science—Mathematics / Computer software / Engineering mathematics / Math Applications in Computer Science / Mathematical & statistical software / Mathematical analysis / Mathematical and Computational Engineering / Mathematical and Computational Engineering Applications / Mathematical Applications in Computer Science / Mathematical optimization / Mathematical Software / Mathematics and Statistics / Maths for computer scientists / Maths for engineers / Optimization
    ISBN:  9783319071237 
    EAN-Code: 
    9783319071237 
    Verlag:  Springer Nature EN 
    Einband:  Gebunden  
    Sprache:  English  
    Dimensionen:  H 235 mm / B 155 mm / D  
    Gewicht:  2560 gr 
    Seiten:  1385 
    Illustration:  XXI, 1385 p. 285 illus., 152 illus. in color. In 2 volumes, not available separately., schwarz-weiss Illustrationen, farbige Illustrationen 
    Zus. Info:  2 Ex. 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    Heuristics are strategies using readily accessible, loosely applicable information to control problem solving. Algorithms, for example, are a type of heuristic. By contrast, Metaheuristics are methods used to design Heuristics and may coordinate the usage of several Heuristics toward the formulation of a single method. GRASP (Greedy Randomized Adaptive Search Procedures) is an example of a Metaheuristic. To the layman, heuristics may be thought of as 'rules of thumb' but despite its imprecision, heuristics is a very rich field that refers to experience-based techniques for problem-solving, learning, and discovery. Any given solution/heuristic is not guaranteed to be optimal but heuristic methodologies are used to speed up the process of finding satisfactory solutions where optimal solutions are impractical. The introduction to this Handbook provides an overview of the history of Heuristics along with main issues regarding the methodologies covered. This is followed by Chapters containing various examples of local searches, search strategies and Metaheuristics, leading to an analyses of Heuristics and search algorithms. The reference concludes with numerous illustrations of the highly applicable nature and implementation of Heuristics in our daily life. Each chapter of this work includes an abstract/introduction with a short description of the methodology. Key words are also necessary as part of top-matter to each chapter to enable maximum search engine optimization. Next, chapters will include discussion of the adaptation of this methodology to solve a difficult optimization problem, and experiments on a set of representative problems.
      



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