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Multi-objective optimization problems = concepts and self-adaptive parameters with mathematical and engineering applications /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Multi-objective optimization problems/ by Fran Sergio Lobato, Valder Steffen Jr.
其他題名:	concepts and self-adaptive parameters with mathematical and engineering applications /
作者:	Lobato, Fran Sergio.
其他作者:	Steffen, Valder.
出版者:	Cham :Springer International Publishing : : 2017.,
面頁冊數:	xx, 160 p. :ill., digital ; : 24 cm.;
Contained By:	Springer eBooks
標題:	Mathematical optimization. -
電子資源:	http://dx.doi.org/10.1007/978-3-319-58565-9
ISBN:	9783319585659

Multi-objective optimization problems = concepts and self-adaptive parameters with mathematical and engineering applications /
Lobato, Fran Sergio.

Multi-objective optimization problemsconcepts and self-adaptive parameters with mathematical and engineering applications /[electronic resource] :by Fran Sergio Lobato, Valder Steffen Jr. - Cham :Springer International Publishing :2017. - xx, 160 p. :ill., digital ;24 cm. - SpringerBriefs in mathematics,2191-8198. - SpringerBriefs in mathematics..

Chapter 1 Introduction -- Part 1 Basic Concepts -- Chapter 2 Multi-objective Optimization Problem -- Chapter 3 Treatment of multi-objective Optimization Problem -- Part 2 Methodology -- Chapter 4 Self-Adaptive Multi-objective Optimization Differential Evolution -- Part 3 Applications -- Chapter 5 Mathematical -- Chapter 6 Engineering -- Part 4 Final Considerations -- Chapter 7 Conclusions.

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.

ISBN: 9783319585659

Standard No.: 10.1007/978-3-319-58565-9doiSubjects--Topical Terms:

527675
Mathematical optimization.

LC Class. No.: QA402.5

Dewey Class. No.: 519.6

Multi-objective optimization problems = concepts and self-adaptive parameters with mathematical and engineering applications /
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