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Using both practical and theoretical points of view, Handbook of Approximation Algorithms and Metaheuristics provides complete coverage of design and approximation methodologies. Tutorial in nature, the book emphasizes techniques that help readers design approximation algorithms using metaheuristic approaches such as simulated annealing, genetic algorithms, ant colony, evolutionary computation, tabu search, and neural networks. Offering a historical perspective, it presents various applications that illustrate many of the techniques included in the text. It also addresses application fields such as bin packaging, traveling sales person problem, Steiner Trees, clustering, and more.