Metaheuristic Search Concepts von Günther Zäpfel | A Tutorial with Applications to Production and Logistics | ISBN 9783642113437

Metaheuristic Search Concepts

A Tutorial with Applications to Production and Logistics

von Günther Zäpfel, Roland Braune und Michael Bögl
Mitwirkende
Autor / AutorinGünther Zäpfel
Autor / AutorinRoland Braune
Autor / AutorinMichael Bögl
Buchcover Metaheuristic Search Concepts | Günther Zäpfel | EAN 9783642113437 | ISBN 3-642-11343-5 | ISBN 978-3-642-11343-7
Leseprobe

Metaheuristic Search Concepts

A Tutorial with Applications to Production and Logistics

von Günther Zäpfel, Roland Braune und Michael Bögl
Mitwirkende
Autor / AutorinGünther Zäpfel
Autor / AutorinRoland Braune
Autor / AutorinMichael Bögl
In many decision problems, e. g. from the area of production and logistics manage ment, the evaluation of alternatives and the determination of an optimal or at least suboptimal solution is an important but dif? cult task. For most such problems no ef? cient algorithm is known and classical approaches of Operations Research like Mixed Integer Linear Programming or Dynamic Pro gramming are often of limited use due to excessive computation time. Therefore, dedicated heuristic solution approaches have been developed which aim at providing good solutions in reasonable time for a given problem. However, such methods have two major drawbacks: First, they are tailored to a speci? c prob lem and their adaption to other problems is dif? cult and in many cases even impos sible. Second, they are typically designed to “build” one single solution in the most effective way, whereas most decision problems have a vast number of feasible solu tions. Hence usually the chances are high that there exist better ones. To overcome these limitations, problem independent search strategies, in particular metaheuris tics, have been proposed. This book provides an elementary step by step introduction to metaheuristics focusing on the search concepts they are based on. The ? rst part demonstrates un derlying concepts of search strategies using a simple example optimization problem.