Ant Colony Optimization (Bradford Books) Review

Average Reviews:

(More customer reviews)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

Click Here to see more reviews about: Ant Colony Optimization (Bradford Books)

Product Description:
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.

Get 20% OFF