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General Meta-heuristic Search Algorithms: Generalised Modelling of Combinatorial Problems - Softcover
Inhaltsangabe
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.
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Reseña del editor
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.
Biografía del autor
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.
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General Meta-heuristic Search Algorithms
Verlag:
VDM Verlag Dr. Müller E.K. Feb 2013, 2013
ISBN 10: 3639267680
ISBN 13: 9783639267686
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Taschenbuch. Zustand: Neu. 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. Artikel-Nr. 9783639267686
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