theory multiobjective optimization (11 résultats)

Paperback. Etat : Brand New. 128 pages. 8.66x5.91x0.29 inches. In Stock.

Taschenbuch. Etat : Neu. Neuware -In this book we present a new optimization algorithm, the proposed algorithm operates in two phases: in the first one, multiobjective version of genetic algorithm is used as search engine in order to generate approximate true Pareto front. This algorithm based on concept of co-evolution and repair algorithm for handling nonlinear constraints. Also it maintains a finite-sized archive of non-dominated solutions which gets iteratively updated in the presence of new solutions based on the concept of ¿-dominance. Then, in the second stage, rough set theory is adopted as local search engine in order to improve the spread of the solutions found so far. The results, provided by the proposed algorithm for benchmark problems, are promising when compared with exiting well-known algorithms. Also, our results suggest that our algorithm is better applicable for solving real-world application problems (Economic Environmental Dispatch of Power Systems).Books on Demand GmbH, Überseering 33, 22297 Hamburg 128 pp. Englisch.

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paperback. Etat : New. Ship out in 2 business day, And Fast shipping, Free Tracking number will be provided after the shipment.Paperback. Pub Date :2013-06-01 Pages: 236 Language: Chinese Publisher: Science Press interval multi-objective optimization problems are endemic and very important. but . there are ways to solve this problem is very small. Interval optimization method using evolutionary multi-objective optimization problems . evolutionary optimization industry in recent years become a hot research directions. Smart Technology Publications Series: interval multi-objective evolutionary optimization theory and a.Four Satisfaction guaranteed,or money back.

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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In this book we present a new optimization algorithm, the proposed algorithm operates in two phases: in the first one, multiobjective version of genetic algorithm is used as search engine in order to generate approximate true Pareto front. This algorithm based on concept of co-evolution and repair algorithm for handling nonlinear constraints. Also it maintains a finite-sized archive of non-dominated solutions which gets iteratively updated in the presence of new solutions based on the concept of -dominance. Then, in the second stage, rough set theory is adopted as local search engine in order to improve the spread of the solutions found so far. The results, provided by the proposed algorithm for benchmark problems, are promising when compared with exiting well-known algorithms. Also, our results suggest that our algorithm is better applicable for solving real-world application problems (Economic Environmental Dispatch of Power Systems). 128 pp. Englisch.

Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Abd Elsameea Hussein MohamedDr. Eng. Mohamed Abd Elsameea Hussein received the B.Sc. degree in Electrical Engineering and M.Sc. ,PhD. in Engineering Mathematics from Faculty of Engineering, Menoufiya University, Egypt. His current re.

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In this book we present a new optimization algorithm, the proposed algorithm operates in two phases: in the first one, multiobjective version of genetic algorithm is used as search engine in order to generate approximate true Pareto front. This algorithm based on concept of co-evolution and repair algorithm for handling nonlinear constraints. Also it maintains a finite-sized archive of non-dominated solutions which gets iteratively updated in the presence of new solutions based on the concept of -dominance. Then, in the second stage, rough set theory is adopted as local search engine in order to improve the spread of the solutions found so far. The results, provided by the proposed algorithm for benchmark problems, are promising when compared with exiting well-known algorithms. Also, our results suggest that our algorithm is better applicable for solving real-world application problems (Economic Environmental Dispatch of Power Systems).

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The aim of intensity modulated radiation therapy (IMRT) is to kill tumor cells while at the same time protecting the surrounding tissue and organs from the damaging effect of radiation. Given the number of beams and beam directions, beam intensity optimization needs to determine beam intensity profiles that yield the best dose distribution under consideration of clinical and physical constraints. In this book, we first review existing mathematical models and computation methods for the beam intensity optimization problem. Then we formulate the beam intensity optimization problem as a multiobjective linear programme (MOLP) with three objectives. The rest of the book is dedicated to developing methods to solve this large MOLP efficiently and to the application in the beam intensity optimization problem. The book provides the necessary mathmatical foundation of multiobjective optimization to solve multiobjective linear programming problems. It is well suitable to be used as a reference book on multiobjective optimization. Moreover it should also be useful to professionals who may be considering using multiobjective optimization.