Metaheuristics for Hard Optimization Metaheuristics for Hard Optimization

Metaheuristics for Hard Optimization

Methods and Case Studies

Johann Dréo والمزيد
    • ‏109٫99 US$
    • ‏109٫99 US$

وصف الناشر

Metaheuristics for Hard Optimization comprises of three parts. The first part is devoted to the detailed presentation of the four most widely known metaheuristics:

• the simulated annealing method,

• tabu search,

• the evolutionary algorithms,

• ant colony algorithms.

Each one of these metaheuristics is actually a family of methods, of which the essential elements are discussed. In the second part, the book presents some other less widespread metaheuristics, then, extensions of metaheuristics and some ways of research are described . The problem of the choice of a metaheuristic is posed and solution methods are discussed. The last part concentrates on three case studies from telecommunications, air traffic control, and vehicle routing.

النوع
علم وطبيعة
تاريخ النشر
٢٠٠٦
١٦ يناير
اللغة
EN
الإنجليزية
عدد الصفحات
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الناشر
Springer Berlin Heidelberg
البائع
Springer Nature B.V.
الحجم
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‫م.ب.‬
Adaptive Representations for Reinforcement Learning Adaptive Representations for Reinforcement Learning
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Issues in the Use of Neural Networks in Information Retrieval Issues in the Use of Neural Networks in Information Retrieval
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Differential Evolution Differential Evolution
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Artificial Neural Networks in Vehicular Pollution Modelling Artificial Neural Networks in Vehicular Pollution Modelling
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Evolutionary Based Solutions for Green Computing Evolutionary Based Solutions for Green Computing
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Computational Intelligence in Expensive Optimization Problems Computational Intelligence in Expensive Optimization Problems
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