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The complex social behaviors of ants have been much studied by science, and computer scientists are now finding that these behavior patterns can provide models for solving difficult combinatorial optimization problems. The attempt to develop algorithms inspired by one aspect of ant behavior, the ability to find what computer scientists would call shortest paths, has become the field of Ant Colony Optimization (ACO), the most successful and widely recognized algorithmic technique based on ant behavior. This book presents an overview of this rapidly growing field, from its theoretical inception to practical applications, including descriptions of many available ACO algorithms and their uses. The book first describes the translation of observed ant behavior into working optimization algorithms. The ant colony metaheuristic is then introduced and viewed in the general context of combinatorial optimization. This is followed by a detailed description and guide to all major ACO algorithms and a report on current theoretical findings. The book surveys ACO applications now in use, including routing, assignment, scheduling, subset, machine learning, and bioinformatics problems. AntNet, an ACO algorithm designed for the network routing problem, is described in detail. The authors conclude by summarizing the progress in the field and outlining future research directions. Each chapter ends with bibliographic material, bullet points setting out important ideas covered in the chapter, and exercises. Ant Colony Optimization will be of interest to academic and industry researchers, graduate students, and practitioners who wish to learn how to implement ACO algorithms.
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The gift of ants to mathematiciansSep 27, 2008 Ant Colony Optimization focuses on the fact that ants foraging for food will quickly form a trail that is the shortest possible ditance betwen the food and home. Rach ant follows the scent trail laid on a path by previous travelers and adds its own pheromone to the scent, both going and coming. With a choice, ants tend to follow the strongest scent. Of a pioneer pair, the one choosing the shortest path will make the round trip before the other. Each pheromone trace evaporates in time, but an ant's antenna can detetct the slightest trace. That is a simplification of the introductory chapters of the book. The "pheromone trail" scheme is used to devise "artificial ant" which then takes part in the comnstruction of powerful ant algorithms for solving intractable problems such as the classical "Traveling Salesman" and other routing problems. The book is a complete text for a college course, with a large bibliography and many internal references to sources on the Internet. It is well written, with pseudo code showing how each algorithm can form computer programs. I can't evaluate the difficulty, but for me the math in later chapters is above my reach, but gratifying, nevertheless.
1 of 3 found the following review helpful:
searching for the basic algorithmsJan 18, 2006 The central idea in the book is to analyse what evolution has provided us. In the form of ants being able to find the shortest path over terrain. This ability has inspired the research described herein.
The book can be read as a fascinating deconstructionist approach to observing and manipulating ant colonies. By trying to look under the observations to discern the fundamental algorithms at work. And then to apply these to such longstanding contexts as the Travelling Salesman Problem.
10 of 10 found the following review helpful:
The intelligence and wisdom of antsApr 28, 2005 Being an ant isn't very complex, but it's a daily fight for life. The losers in that fight don't count, but the winners get to vote.
That is the basis of ant colony optimization. There are many parts to the idea, all of them very simple. First, there are many routes to the goal (food, if you're an ant) - some are better, some worse, you don't know which are which in advance, and the answer may change over time. Second, it's a random search. If you find any answer at all, no matter how convoluted, you get to vote on your route. Third, there are many other ants, all voting. Any leg of a trip that is heavily followed must be part of a good route, and gets many votes. There are details, but that's about it.
Chapters 1-3 are the most readable, and convey the basic spirit of the family of algorithms. Ch. 4-6 will drag a bit, for the general reader, but go into significant detail about the ant algorithm and specific applications.
Ch. 7 ends the book with a warm, informal discussion of the algorithm's history and some delightful variations. Dorigo, the principal author and founder of the ant school, uses this chapter to express his pure joy at having found such a wonderful thing, and at the similar approaches that others have also found.
The approach has some real limits. For example, it can solve only problems that look like finding the shortest route. The good news is that a wide range of unlikely problems can all be cast in these terms. The better news is that, given the many variations available, some form of the 'stigmergic' approach will probably solve any problem in that range. Best of all, though, is the sheer cleverness and the sincere appreciation expressed by the authors.
Nature is economical, but a brilliant problem solver. This is written by someone who as able to listen in on one of the lessons.
//wiredweird
10 of 10 found the following review helpful:
A comprehensive and very readable introductionOct 04, 2004 Fifteen years after the elegant double-bridge experiments by Deneubourg et al. that formed the basis of the Ant Colony Optimization algorithm, Marco Dorigo, the inventor of ACO, and Thomas Stützle, an expert on stochastic local search methods, have pooled their knowledge to summarize the current state of the art.
This book gives a well paced introduction to ACO, describes its use in various optimization problems and gives interesting examples of its applications in industry. Explanations are clear and concise and, with the exception of a few well defined technical terms, free of scientific jargon. It is a pleasure to read for everyone with an interest in optimization theory. However, if you are looking for a book that celebrates the beauty of nature's problem solving capabilities, you are better of with "Swarm Intelligence" or Flake's "Computational Beauty of Nature". The initial idea of ACO may be bio-inspired, but this book has a crystal clear focus of the computational considerations in optimization theory.
7 of 9 found the following review helpful:
A fine compilationSep 03, 2004 This book is a fine compilation of what have been done with the Ant Colony paradigm so far. Highly readable, even for people without previous experience in the field of optimization.
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