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2018 | OriginalPaper | Buchkapitel

13. Ant Colony Optimization: A Component-Wise Overview

verfasst von : Manuel López-Ibáñez, Thomas Stützle, Marco Dorigo

Erschienen in: Handbook of Heuristics

Verlag: Springer International Publishing

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Abstract

The indirect communication and foraging behavior of certain species of ants have inspired a number of optimization algorithms for NP-hard problems. These algorithms are nowadays collectively known as the ant colony optimization (ACO) metaheuristic. This chapter gives an overview of the history of ACO, explains in detail its algorithmic components, and summarizes its key characteristics. In addition, the chapter introduces a software framework that unifies the implementation of these ACO algorithms for two example problems, the traveling salesman problem and the quadratic assignment problem. By configuring the parameters of the framework, one can combine features from various ACO algorithms in novel ways. Examples on how to find a good configuration automatically are given in the chapter. The chapter closes with a review of combinations of ACO with other techniques and extensions of the ACO metaheuristic to other problem classes.

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Vorheriges Kapitel Variable Neighborhood Descent
Nächstes Kapitel Evolutionary Algorithms
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Metadaten
Titel
Ant Colony Optimization: A Component-Wise Overview
verfasst von
Manuel López-Ibáñez
Thomas Stützle
Marco Dorigo
Copyright-Jahr
2018
Buch
Handbook of Heuristics

Print ISBN: 978-3-319-07123-7

Electronic ISBN: 978-3-319-07124-4

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-3-319-07124-4_21

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