2014•Unpublished venueRequires access

Variants of Ant Colony Optimization: A Metaheuristic for Solving the Traveling Salesman Problem

Oscar Humberto Montiel Ross, Roberto Sepulveda

Abstract

There are different algorithms based on the simulation of natural processes and genetics such as genetic algorithm s and Ant Colony Optimization (ACO), based on heuristic problem solving (Bianchi et al. 2002). Nowadays, ACO is used to solve more complex problems, which require a lot of processing time for achieving results (Barán and Sosa 2000). Therefore, we can work with highly complex problems getting results with less processing time with a parallel implementation. In this paper, we describe several variants of Ant Colony Optimization (ACO) to solve the Traveling Salesman Problem (TSP) allowing the user to input parameters using a graphical interface and performing parallel processing.

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Key concepts: Travelling salesman problem, Ant colony optimization algorithms, Metaheuristic, Parallel metaheuristic, ANT, Mathematical optimization, Computer science, Extremal optimization