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A taxonomy and an empirical analysis of multiple objective ant colony optimization algorithms for the bi-criteria TSP [An article from: European Journal of Operational Research]

Author C. Garcia-Martinez, O. Cordon, F. Herrera
Publisher Elsevier
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Book Details
PublisherElsevier
ISBN / ASINB000PDSPMW
ISBN-13978B000PDSPM2
AvailabilityAvailable for download now
MarketplaceUnited States 🇺🇸

Description

This digital document is a journal article from European Journal of Operational Research, published by Elsevier in 2007. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

Description:
The difficulty to solve multiple objective combinatorial optimization problems with traditional techniques has urged researchers to look for alternative, better performing approaches for them. Recently, several algorithms have been proposed which are based on the ant colony optimization metaheuristic. In this contribution, the existing algorithms of this kind are reviewed and a proposal of a taxonomy for them is presented. In addition, an empirical analysis is developed by analyzing their performance on several instances of the bi-criteria traveling salesman problem in comparison with two well-known multi-objective genetic algorithms.