Metaheuristics for Hard Optimization

Beschreibung

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.

This text presents a family of advanced methods of optimization called Metaheuristics.
It covers a range of topics including simulated annealing, tabu search, evolutionary and genetic algorithms, and ant colony optimization. The book contains various case studies from engineering and operations research, and includes commented literature for each chapter.

Autor*in

Johann Dréo

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algorithm algorithms communication evolutionary algorithm genetic algorithms metaheuristic modeling operations research optimization programming Engineering Economics

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