General Meta-heuristic Search Algorithms

Marcus Randall

ISBN 10: 3639267680 / ISBN 13: 9783639267686

Published by VDM Verlag Dr. Müller E.K. Feb 2013, 2013

About this Item

Neuware -In recent years, there have been many studies in which tailored heuristics and meta-heuristics have been applied to specific optimisation problems. These algorithms can be extremely efficient, but may also lack generality. In contrast, the research outlined in this monograph focuses on building a general-purpose combinatorial optimisation problem solver using a variety of meta-heuristic algorithms including Simulated Annealing and Tabu Search. The work is novel because it uses a modelling environment in which the solution is stored in dense dynamic list structures, unlike a more conventional sparse vector notation. Because of this, it incorporates a number of neighbourhood search operators that are normally only found in tailored algorithms and it performs well on a range of problems. The general nature of the outlined system allows a model developer to rapidly prototype different problems. The results indicate that the system achieves good performance in terms of solution quality and runtime on a range of combinatorial problems.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 216 pp. Englisch.

Seller Inventory # 9783639267686

Bibliographic Details

• Title: General Meta-heuristic Search Algorithms
• Publisher: VDM Verlag Dr. Müller E.K. Feb 2013
• Publication Date: 2013
• Language: English
• ISBN 10: 3639267680
• ISBN 13: 9783639267686
• Binding: Taschenbuch
• Condition: Neu

About this title

Synopsis

In recent years, there have been many studies in which tailored heuristics and meta-heuristics have been applied to specific optimisation problems. These algorithms can be extremely efficient, but may also lack generality. In contrast, the research outlined in this monograph focuses on building a general-purpose combinatorial optimisation problem solver using a variety of meta-heuristic algorithms including Simulated Annealing and Tabu Search. The work is novel because it uses a modelling environment in which the solution is stored in dense dynamic list structures, unlike a more conventional sparse vector notation. Because of this, it incorporates a number of neighbourhood search operators that are normally only found in tailored algorithms and it performs well on a range of problems. The general nature of the outlined system allows a model developer to rapidly prototype different problems. The results indicate that the system achieves good performance in terms of solution quality and runtime on a range of combinatorial problems.

About the Author

Dr Randall is an associate professor at Bond University, Australia. He is a computer scientist with research interests in combinatorial optimisation, heuristics and search algorithms. Marcus has also published over sixty peer reviewed works including a number of books, chapters for books, journal and conference articles.