Multi-Objective Optimization Problems [electronic resource] : Concepts and Self-Adaptive Parameters with Mathematical and Engineering Applications / by Fran Sérgio Lobato, Valder Steffen Jr.

За: Інтелектуальна відповідальність: Вид матеріалу: Текст Серія: SpringerBriefs in MathematicsПублікація: Cham : Springer International Publishing : Imprint: Springer, 2017Видання: 1st ed. 2017Опис: XX, 160 p. 103 illus., 75 illus. in color. online resourceТип вмісту:
  • text
Тип засобу:
  • computer
Тип носія:
  • online resource
ISBN:
  • 9783319585659
Тематика(и): Додаткові фізичні формати: Printed edition:: Немає назви; Printed edition:: Немає назвиДесяткова класифікація Дьюї:
  • 519.6 23
Класифікація Бібліотеки Конгресу:
  • QA402.5-402.6
Електронне місцезнаходження та доступ:
Вміст:
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.
У: Springer eBooksЗведення: 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.
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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.

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