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Review of How to Solve It: Modern Heuristics: Zbigniew Michalewicz and David B Fogel

Published: 01 March 2001 Publication History

Abstract

How to Solve It is a friendly gem of a book which introduces the basic principles of traditional optimization, evolutionary optimization, neural nets, and fuzzy methods. In the spirit of Polya's classic of the same name, the authors emphasize the "how and why" of the problem-solving process, constantly prodding the reader to stop and solve subproblems, or come up with new heuristics, or indeed question whether or not the problem has been posed correctly in the first place.This book is clear, concise, and fun to read. It is not a handbook of heuristics, but rather an accessible high-level overview of the pros, cons, and applicability of the major categories of heuristic methods, with particular emphasis on optimization methods utilizing evolutionary computation. The presentation is lucid, and the authors do a good job of picking out key properties of algorithms and problem domains. The only prerequisites are basic mathematics and some problem-solving talent.

References

[1]
Evolutionary Computation 1 and 2.Edited by Back, Fogel, and Michalewicz; 2000.
[2]
FOGA.Foundations of Genetic Algorithms; biennial conference.
[3]
Genetic Programming I, II, III.Authored by John Koza; 1992, 1994, and 1999.
[4]
Hitchhiker's Guide to Evolutionary Computation.alife.santafe.edu/joke/encore/www/

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Published In

cover image ACM SIGACT News
ACM SIGACT News  Volume 32, Issue 1
March 2001
88 pages
ISSN:0163-5700
DOI:10.1145/568438
Issue’s Table of Contents
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 March 2001
Published in SIGACT Volume 32, Issue 1

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Cited By

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  • (2021)Hybrid Bird Mating Optimizer With Single-Based Algorithms for Combinatorial Optimization ProblemsIEEE Access10.1109/ACCESS.2021.31021549(115972-115989)Online publication date: 2021
  • (2020)Bird Mating Optimizer for Combinatorial Optimization ProblemsIEEE Access10.1109/ACCESS.2020.29934918(96845-96858)Online publication date: 2020
  • (2019)StructOpt: A modular materials structure optimization suite incorporating experimental data and simulated energiesComputational Materials Science10.1016/j.commatsci.2018.12.052160(1-8)Online publication date: Apr-2019
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