Evolution of Ant Colony Optimization Algorithm -- A Brief Literature Review

August 15, 2019 ยท Declared Dead ยท ๐Ÿ› arXiv.org

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Authors Aleem Akhtar arXiv ID 1908.08007 Category cs.NE: Neural & Evolutionary Cross-listed cs.AI Citations 27 Venue arXiv.org Last Checked 3 months ago
Abstract
Ant Colony Optimization (ACO) is a metaheuristic proposed by Marco Dorigo in 1991 based on behavior of biological ants. Pheromone laying and selection of shortest route with the help of pheromone inspired development of first ACO algorithm. Since, presentation of first such algorithm, many researchers have worked and published their research in this field. Though initial results were not so promising but recent developments have made this metaheuristic a significant algorithm in Swarm Intelligence. This research presents a brief overview of recent developments carried out in ACO algorithms in terms of both applications and algorithmic developments. For application developments, multi-objective optimization, continuous optimization and time-varying NP-hard problems have been presented. While to review articles based on algorithmic development, hybridization and parallel architectures have been investigated.
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