Modern Optimization with R

Paulo Cortez

ISBN 10: 3030728188 / ISBN 13: 9783030728182

Published by Springer, Springer, 2021

About this Item

Druck auf Anfrage Neuware - Printed after ordering - The goal of this book is to gather in a single work the most relevant concepts related in optimization methods, showing how such theories 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.This new edition integrates the latest R packages through text and code examples. It also discusses new topics, such as: the impact of artificial intelligence and business analytics in modern optimization tasks; the creation of interactive Web applications; usage of parallel computing; and more modern optimization algorithms (e.g., iterated racing, ant colony optimization, grammatical evolution).

Seller Inventory # 9783030728182

Bibliographic Details

• Title: Modern Optimization with R
• Publisher: Springer, Springer
• Publication Date: 2021
• Language: English
• ISBN 10: 3030728188
• ISBN 13: 9783030728182
• Binding: Taschenbuch
• Edition: 2nd Edition
• Condition: Neu
• Dimensions: 235W x 155H x 15D millimeters 235 millimeters width by 155 millimeters height by 15 millimeters depth
• Weight: 417 grams

About this title

Synopsis

The goal of this book is to gather in a single work the most relevant concepts related in optimization methods, showing how such theories 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.

This new edition integrates the latest R packages through text and code examples. It also discusses new topics, such as: the impact of artificial intelligence and business analytics in modern optimization tasks; the creation of interactive Web applications; usage of parallel computing; and more modern optimization algorithms (e.g., iterated racing, ant colony optimization, grammatical evolution). 

About the Author

Paulo Cortez (Habilitation, PhD) is an Associate Professor (with tenure) at the Department of Information Systems, University of Minho, Portugal. He is also assistant director of the ALGORITMI R&D Centre. From 2012 to 2015, he was Vice-President of the Portuguese Association for Artificial Intelligence (www.appia.pt). Currently, he is Associate Editor of the journals Decision Support Systems and Expert Systems. His research, within the fields of decision support, data science, business analytics, machine learning, and modern optimization, has appeared in Journal of Heuristics, Decision Support Systems, Information Processing and Management, Information Sciences and others.