Modern optimization with R
Author(s)
Bibliographic Information
Modern optimization with R
（Use R! / series editors, Robert Gentleman, Kurt Hornik, Giovanni Parmigiani）
Springer, c2014
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Note
Includes bibliographical references (p. 149-151) and index
Description and Table of Contents
Description
The goal of this book is to gather in a single document the most relevant concepts related to modern optimization methods, showing how such concepts and methods can be addressed using the open source, multi-platform R tool. Modern optimization methods, also known as metaheuristics, are particularly useful for solving complex problems for which no specialized optimization algorithm has been developed. These methods often yield high quality solutions with a more reasonable use of computational resources (e.g. memory and processing effort). Examples of popular modern methods discussed in this book are: simulated annealing; tabu search; genetic algorithms; differential evolution; and particle swarm optimization. This book is suitable for undergraduate and graduate students in Computer Science, Information Technology, and related areas, as well as data analysts interested in exploring modern optimization methods using R.
Table of Contents
1. Introduction.- 2. R Basics.- 3. Blind Search.- 4. Local Search.- 5. Population-Based Search.- 6. Multi-Objective Optimization.- 7. Applications.
by "Nielsen BookData"
