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α-Nearness Ant Colony System with Adaptive Strategies and Performance Analysis Cover

α-Nearness Ant Colony System with Adaptive Strategies and Performance Analysis

By: Jinqiu Lv,  Xiaoming You and  Sheng Liu  
Open Access
|Mar 2015

Abstract

This paper proposes an improved ant colony system with adaptive strategies, called α

-AACS and considers its performance. First of all, we introduce α-nearness based on the minimum 1-tree for the disadvantage of the Ant Colony System (ACS), which better reflects the chances of a given link, being a member of an optimal tour. Next, we utilize the adaptive operator to balance the population diversity and the convergence speed and propose other optimizations for ACS. Finally, we present an account of the experiments and the statistic-based analysis, which clearly shows that α-AACS has a better global searching ability in finding the best solutions and better performance in solution variation.

DOI: https://doi.org/10.1515/cait-2015-0001 | Journal eISSN: 1314-4081 | Journal ISSN: 1311-9702
Language: English
Page range: 3 - 13
Published on: Mar 13, 2015
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2015 Jinqiu Lv, Xiaoming You, Sheng Liu, published by Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.