Greiner D Evolutionary Algorithms in Engineering Design Optimization 2022 | 41.29 MB
English | 316 Pages
Title: A9Rpqxnsa_1ueiatt_67o.tmp
Author: MDPI
Year: 2021
Description:
Based on course-tested material, this rigorous yet accessible graduate textbook covers both fundamental and advanced optimization theory and algorithms. It covers a wide range of numerical methods and topics, including both gradient-based and gradient-free algorithms, multidisciplinary design optimization, and uncertainty, with instruction on how to determine which algorithm should be used for a given application. It also provides an overview of models and how to prepare them for use with numerical optimization, including derivative computation. Over 400 high-quality visualizations and numerous examples facilitate understanding of the theory, and practical tips address common issues encountered in practical engineering design optimization and how to address them. Numerous end-of-chapter homework problems, progressing in difficulty, help put knowledge into practice. Accompanied online by a solutions manual for instructors and source code for problems, this is ideal for a one- or two-semester graduate course on optimization in aerospace, civil, mechanical, electrical, and chemical engineering departments.
DOWNLOAD:
https://rapidgator.net/file/74a6880a7fdcdb8e477ca1f6047d6e11/Greiner_D._Evolutionary_Algorithms_in_Engineering_Design_Optimization_2022.rar
https://uploadgig.com/file/download/0a225e1a244D1b58/Greiner_D._Evolutionary_Algorithms_in_Engineering_Design_Optimization_2022.rar
Based on course-tested material, this rigorous yet accessible graduate textbook covers both fundamental and advanced optimization theory and algorithms. It covers a wide range of numerical methods and topics, including both gradient-based and gradient-free algorithms, multidisciplinary design optimization, and uncertainty, with instruction on how to determine which algorithm should be used for a given application. It also provides an overview of models and how to prepare them for use with numerical optimization, including derivative computation. Over 400 high-quality visualizations and numerous examples facilitate understanding of the theory, and practical tips address common issues encountered in practical engineering design optimization and how to address them. Numerous end-of-chapter homework problems, progressing in difficulty, help put knowledge into practice. Accompanied online by a solutions manual for instructors and source code for problems, this is ideal for a one- or two-semester graduate course on optimization in aerospace, civil, mechanical, electrical, and chemical engineering departments.
DOWNLOAD:
https://rapidgator.net/file/74a6880a7fdcdb8e477ca1f6047d6e11/Greiner_D._Evolutionary_Algorithms_in_Engineering_Design_Optimization_2022.rar
https://uploadgig.com/file/download/0a225e1a244D1b58/Greiner_D._Evolutionary_Algorithms_in_Engineering_Design_Optimization_2022.rar
