Engineering Optimization: An Introduction with Metaheuristic Applications
| Author | : | |
| Rating | : | 4.86 (562 Votes) |
| Asin | : | 0470582464 |
| Format Type | : | paperback |
| Number of Pages | : | 347 Pages |
| Publish Date | : | 2016-02-04 |
| Language | : | English |
DESCRIPTION:
Good Introduction for engineers. Bad Kindle format Tony This is a good introduction to optimization for those who have not been exposed to the material before. The author makes the material enjoyable, but it lacks proofs and other in-depth descriptions that students of optimization theory would need. Nevertheless, there are plenty of examples to help undestand the concept.The problem I had is with the Kindle version. The are several chapters in which the formulas are located at the incorrect places. You can figure it out, but this makes it very painful to read. This is the second time. Very good and handy book Markos I am very happy to have this "optimally designed" book for a learner. It describes the optmization theories and formulas with few steps and supported by easy to understand worked examples. One does not have to sift through pages after pages of this book only to understand the core matters. As an optimization instructor i am attracted by the style of writing and how easy it is to communicate students through such texts with minimum number of pages delivering maximum amount of knowledge.. Great Book Just what I expected.
XIN-SHE YANG, PhD, is Senior Research Fellow in the Department of Engineering at Cambridge University (United Kingdom). Yang has published more than sixty journal articles in his areas of research interest, which include computational mathematics, metaheuristic algorithms, numerical analysis, and engineering optimization. The Editor-in-Chief of International Journal of Mathematical Modeling and Numerical Optimization (IJMMNO), Dr.
In addition, references to the current literature enable readers to investigate individual algorithms and methods in greater detail.Engineering Optimization: An Introduction with Metaheuristic Applications is an excellent book for courses on optimization and computer simulation at the upper-undergraduate and graduate levels. It is also a valuable reference for researchers and practitioners working in the fields of mathematics, engineering, computer science, operations research, and management science who use metaheuristic algorithms to solve problems in their everyday work.. With insightful examples from various fields of study, the author highlights key concepts and techniques for the successful application of commonly-used metaheuristc algorithms, including simulated annealing, particle swarm optimization, harmony search, and genetic algorithms.The author introduces all major metaheuristic algorithms and their applications in optimization through a presentation that is organized into three succinct parts:Foundations of Optimization and Algorithms provides a brief introduction to the underlying nature of optimization and the common approaches to optimization problems, random number generation, the Monte Carlo method, and the Markov chain Monte Carlo methodMetaheuristic Algorithms presents common metaheuristic algorithms in detail, including genetic algorithms, simulated annealing, ant algorithms, bee algorithms, particle
The Editor-in-Chief of International Journal of Mathematical Modeling and Numerical Optimization (IJMMNO), Dr. Yang has published more than sixty journal articles in his areas of research interest, which include computational mathematics, metaheuristic algorithms, numerical analysis, and engineering optimization. About the AuthorXIN-SHE YANG, PhD, is Senior Research Fellow in the Department of Engineering at Cambridge University (United Kingdom).