Modern Optimization with R

1. Front Matter

   Pages i-xiii

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2. Introduction

   • Paulo Cortez

   Pages 1-9

3. R Basics

   • Paulo Cortez

   Pages 11-30

4. Blind Search

   • Paulo Cortez

   Pages 31-43

5. Local Search

   • Paulo Cortez

   Pages 45-61

6. Population Based Search

   • Paulo Cortez

   Pages 63-98

7. Multi-Objective Optimization

   • Paulo Cortez

   Pages 99-117

8. Applications

   • Paulo Cortez

   Pages 119-147

9. Back Matter

   Pages 149-174

   PDF

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.

• R statistical tool
• evolutionary computation
• metaheuristics
• particle swarm optimization
• simulated annealing
• tabu search

• Department of Information Systems, University of Minho, Guimarães, Portugal

  Paulo Cortez

Paulo Cortez is an associate professor in the Department of Information Systems at the University of Minho, Portugal. 

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