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Paperback. Condition: Brand New. 160 pages. 9.00x6.00x0.50 inches. In Stock.
Language: English
Published by Springer, Palgrave Macmillan, 2017
ISBN 10: 3319585649 ISBN 13: 9783319585642
Seller: AHA-BUCH GmbH, Einbeck, Germany
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is aimed at undergraduate and graduate students inapplied mathematics or computer science, as a tool for solving real-world design problems. The present work covers fundamentals in multi-objective optimization and applications in mathematical and engineering system designusing a new optimization strategy, namely the Self-Adaptive Multi-objective Optimization Differential Evolution (SA-MODE) algorithm. This strategy is proposed in order to reduce the number of evaluations of the objective function through dynamic update of canonical Differential Evolution parameters (population size, crossover probability and perturbation rate). The methodology is applied to solve mathematical functions considering test cases from the literature and various engineering systems design, such as cantilevered beam design, biochemical reactor, crystallization process, machine tool spindle design, rotary dryer design, among others.
Taschenbuch. Condition: Neu. Multi-Objective Optimization Problems | Concepts and Self-Adaptive Parameters with Mathematical and Engineering Applications | Fran Sérgio Lobato (u. a.) | Taschenbuch | SpringerBriefs in Mathematics | xx | Englisch | 2017 | Springer | EAN 9783319585642 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Condition: new. Questo è un articolo print on demand.
Language: English
Published by Springer International Publishing Jul 2017, 2017
ISBN 10: 3319585649 ISBN 13: 9783319585642
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book is aimed at undergraduate and graduate students inapplied mathematics or computer science, as a tool for solving real-world design problems. The present work covers fundamentals in multi-objective optimization and applications in mathematical and engineering system designusing a new optimization strategy, namely the Self-Adaptive Multi-objective Optimization Differential Evolution (SA-MODE) algorithm. This strategy is proposed in order to reduce the number of evaluations of the objective function through dynamic update of canonical Differential Evolution parameters (population size, crossover probability and perturbation rate). The methodology is applied to solve mathematical functions considering test cases from the literature and various engineering systems design, such as cantilevered beam design, biochemical reactor, crystallization process, machine tool spindle design, rotary dryer design, among others. 180 pp. Englisch.
Language: English
Published by Springer International Publishing, 2017
ISBN 10: 3319585649 ISBN 13: 9783319585642
Seller: moluna, Greven, Germany
Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Offers an starting point to key concepts related to multi-objective optimization problemsBrings a rich variety of applications in Engineering and MathematicsPresents a new optimization strategy, the S.
Language: English
Published by Springer, Palgrave Macmillan Jul 2017, 2017
ISBN 10: 3319585649 ISBN 13: 9783319585642
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book is aimed at undergraduate and graduate students in applied mathematics or computer science, as a tool for solving real-world design problems. The present work covers fundamentals in multi-objective optimization and applications in mathematical and engineering system design using a new optimization strategy, namely the Self-Adaptive Multi-objective Optimization Differential Evolution (SA-MODE) algorithm. This strategy is proposed in order to reduce the number of evaluations of the objective function through dynamic update of canonical Differential Evolution parameters (population size, crossover probability and perturbation rate). The methodology is applied to solve mathematical functions considering test cases from the literature and various engineering systems design, such as cantilevered beam design, biochemical reactor, crystallization process, machine tool spindle design, rotary dryer design, among others.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 180 pp. Englisch.