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An Adaptive Hybrid Genetic Algorithm ? Simulated Annealing Approach: A New Hybridization Technique Applied to Solving the MAP Problem in Bayesian Belief Networks - Softcover
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Genetic algorithms (GAs) and simulated annealing (SA) are important search methods. Combining both may improve the search quality, for example by using SA as a genetic operator. One problem in such technique is to find annealing parameters that work for all stages of the run. In this research, we introduce a new adaptive hybrid GA-SA algorithm, in which SA acts as a mutation. However, the SA will be adaptive in the sense that its parameters are evolved during the search. Adaptation should help guide the search towards optimum solutions with minimum parameter tuning. The algorithm is tested on solving an important NP-hard problem, the MAP (Maximum a-Posteriori) Assignment Problem on BBNs (Bayesian Belief Networks). The results obtained indicate that the adaptive hybrid algorithm provides an improvement of solution quality over that obtained by GA used alone and GA augmented with standard non-adaptive SA. Its effect, however, is more profound for large problems, which are difficult for GA alone to solve. The techniques reported in this book should be of interest to researchers in heuristics and meta-heuristics, and their application to combinatorial optimization problems.
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An Adaptive Hybrid Genetic Algorithm - Simulated Annealing Approach
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VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2010
ISBN 10: 3838335295
ISBN 13: 9783838335292
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An Adaptive Hybrid Genetic Algorithm ¿ Simulated Annealing Approach
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LAP LAMBERT Academic Publishing Dez 2009, 2009
ISBN 10: 3838335295
ISBN 13: 9783838335292
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Genetic algorithms (GAs) and simulated annealing (SA) are important search methods. Combining both may improve the search quality, for example by using SA as a genetic operator. One problem in such technique is to find annealing parameters that work for all stages of the run. In this research, we introduce a new adaptive hybrid GA-SA algorithm, in which SA acts as a mutation. However, the SA will be adaptive in the sense that its parameters are evolved during the search. Adaptation should help guide the search towards optimum solutions with minimum parameter tuning. The algorithm is tested on solving an important NP-hard problem, the MAP (Maximum a-Posteriori) Assignment Problem on BBNs (Bayesian Belief Networks). The results obtained indicate that the adaptive hybrid algorithm provides an improvement of solution quality over that obtained by GA used alone and GA augmented with standard non-adaptive SA. Its effect, however, is more profound for large problems, which are difficult for GA alone to solve. The techniques reported in this book should be of interest to researchers in heuristics and meta-heuristics, and their application to combinatorial optimization problems. 176 pp. Englisch. Seller Inventory # 9783838335292
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An Adaptive Hybrid Genetic Algorithm - Simulated Annealing Approach
Published by
VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2010
ISBN 10: 3838335295
ISBN 13: 9783838335292
New
Softcover
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An Adaptive Hybrid Genetic Algorithm - Simulated Annealing Approach
Published by
LAP Lambert Academic Publishing, 2009
ISBN 10: 3838335295
ISBN 13: 9783838335292
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Genetic algorithms (GAs) and simulated annealing (SA) are important search methods. Combining both may improve the search quality, for example by using SA as a genetic operator. One problem in such technique is to find annealing parameters that work for all. Seller Inventory # 5414098
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An Adaptive Hybrid Genetic Algorithm - Simulated Annealing Approach
Published by
VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2010
ISBN 10: 3838335295
ISBN 13: 9783838335292
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Softcover
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Condition: New. PRINT ON DEMAND pp. 176. Seller Inventory # 18128847178
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An Adaptive Hybrid Genetic Algorithm - Simulated Annealing Approach
Published by
LAP LAMBERT Academic Publishing Dez 2009, 2009
ISBN 10: 3838335295
ISBN 13: 9783838335292
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Taschenbuch
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Genetic algorithms (GAs) and simulated annealing (SA) are important search methods. Combining both may improve the search quality, for example by using SA as a genetic operator. One problem in such technique is to find annealing parameters that work for all stages of the run. In this research, we introduce a new adaptive hybrid GA-SA algorithm, in which SA acts as a mutation. However, the SA will be adaptive in the sense that its parameters are evolved during the search. Adaptation should help guide the search towards optimum solutions with minimum parameter tuning. The algorithm is tested on solving an important NP-hard problem, the MAP (Maximum a-Posteriori) Assignment Problem on BBNs (Bayesian Belief Networks). The results obtained indicate that the adaptive hybrid algorithm provides an improvement of solution quality over that obtained by GA used alone and GA augmented with standard non-adaptive SA. Its effect, however, is more profound for large problems, which are difficult for GA alone to solve. The techniques reported in this book should be of interest to researchers in heuristics and meta-heuristics, and their application to combinatorial optimization problems.Books on Demand GmbH, Überseering 33, 22297 Hamburg 176 pp. Englisch. Seller Inventory # 9783838335292
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An Adaptive Hybrid Genetic Algorithm ¿ Simulated Annealing Approach : A New Hybridization Technique Applied to Solving the MAP Problem in Bayesian Belief Networks
Published by
LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3838335295
ISBN 13: 9783838335292
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Taschenbuch
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Genetic algorithms (GAs) and simulated annealing (SA) are important search methods. Combining both may improve the search quality, for example by using SA as a genetic operator. One problem in such technique is to find annealing parameters that work for all stages of the run. In this research, we introduce a new adaptive hybrid GA-SA algorithm, in which SA acts as a mutation. However, the SA will be adaptive in the sense that its parameters are evolved during the search. Adaptation should help guide the search towards optimum solutions with minimum parameter tuning. The algorithm is tested on solving an important NP-hard problem, the MAP (Maximum a-Posteriori) Assignment Problem on BBNs (Bayesian Belief Networks). The results obtained indicate that the adaptive hybrid algorithm provides an improvement of solution quality over that obtained by GA used alone and GA augmented with standard non-adaptive SA. Its effect, however, is more profound for large problems, which are difficult for GA alone to solve. The techniques reported in this book should be of interest to researchers in heuristics and meta-heuristics, and their application to combinatorial optimization problems. Seller Inventory # 9783838335292
Quantity: 1 available
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An Adaptive Hybrid Genetic Algorithm Simulated Annealing Approach: A New Hybridization Technique Applied to Solving the MAP Problem in Bayesian Belief Networks
Published by
LAP Lambert Academic Publishing, 2010
ISBN 10: 3838335295
ISBN 13: 9783838335292
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