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View details for this title. Artificial Intelligence, Evolutionary Computing and Metaheuristics: In the Footsteps of Alan Turing Hardback, ed.
An accessible introduction to metaheuristics and optimization, featuring powerful and modern algorithms for application across engineering. Highlighting the latest developments that have evolved in recent years, Engineering Optimization: An Introduction with Metaheuristic Applications outlines.
Studies in Computational Intelligence. Simulation-Driven Modeling and Optimization: Springer Proceedings in Mathematics and Statistics.
Added to Your Shopping Cart. Description An accessible introduction to metaheuristics and optimization, featuring powerful and modern algorithms for application across engineering and the sciences From engineering and computer science to economics and management science, optimization is a core component for problem solving. 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 method Metaheuristic Algorithms presents common metaheuristic algorithms in detail, including genetic algorithms, simulated annealing, ant algorithms, bee algorithms, particle swarm optimization, firefly algorithms, and harmony search Applications outlines a wide range of applications that use metaheuristic algorithms to solve challenging optimization problems with detailed implementation while also introducing various modifications used for multi-objective optimization Throughout the book, the author presents worked-out examples and real-world applications that illustrate the modern relevance of the topic.
An Introduction with Metaheuristic Applications 4. In addition, referencesto the current literature enable readers to investigate individualalgorithms and methods in greater detail. 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. Cinthya Solano marked it as to-read Sep 08, Tanachapong Wangkhamhan marked it as to-read Feb 22, Goodreads helps you keep track of books you want to read. Saida Charak marked it as to-read Jun 29,
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. Permissions Request permission to reuse content from this site.
Table of contents List of Figures.