Iterative Computer Algorithms With Applications In Engineering
Download Iterative Computer Algorithms With Applications In Engineering PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Iterative Computer Algorithms With Applications In Engineering book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Iterative Computer Algorithms with Applications in Engineering
Author: Sadiq M. Sait
language: en
Publisher: Wiley-IEEE Computer Society Press
Release Date: 1999
The book includes an introduction to fuzzy logic and its application in the formulation of multi-objective optimization problems, a discussion on hybrid techniques that combine features of heuristics, a survey of recent research work, and examples that illustrate required mathematical concepts."--BOOK JACKET.
Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms
The digital age is ripe with emerging advances and applications in technological innovations. Mimicking the structure of complex systems in nature can provide new ideas on how to organize mechanical and personal systems. The Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms is an essential scholarly resource on current algorithms that have been inspired by the natural world. Featuring coverage on diverse topics such as cellular automata, simulated annealing, genetic programming, and differential evolution, this reference publication is ideal for scientists, biological engineers, academics, students, and researchers that are interested in discovering what models from nature influence the current technology-centric world.
Evolutionary Algorithms for Solving Multi-Objective Problems
Author: Carlos Coello Coello
language: en
Publisher: Springer Science & Business Media
Release Date: 2007-08-26
Solving multi-objective problems is an evolving effort, and computer science and other related disciplines have given rise to many powerful deterministic and stochastic techniques for addressing these large-dimensional optimization problems. Evolutionary algorithms are one such generic stochastic approach that has proven to be successful and widely applicable in solving both single-objective and multi-objective problems. This textbook is a second edition of Evolutionary Algorithms for Solving Multi-Objective Problems, significantly expanded and adapted for the classroom. The various features of multi-objective evolutionary algorithms are presented here in an innovative and student-friendly fashion, incorporating state-of-the-art research. The book disseminates the application of evolutionary algorithm techniques to a variety of practical problems, including test suites with associated performance based on a variety of appropriate metrics, as well as serial and parallel algorithm implementations.