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2018 | OriginalPaper | Chapter

13. Ant Colony Optimization: A Component-Wise Overview

Authors: Manuel López-Ibáñez, Thomas Stützle, Marco Dorigo

Published in: Handbook of Heuristics

Publisher: 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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Metadata
Title
Ant Colony Optimization: A Component-Wise Overview
Authors
Manuel López-Ibáñez
Thomas Stützle
Marco Dorigo
Copyright Year
2018
DOI
https://doi.org/10.1007/978-3-319-07124-4_21

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