Some Analytical Considerations Regarding the Traveling Salesman Problem Solved with Wolfram Mathematica Applications

Main Article Content

Bogdan-Vasile Cioruța
Alexandru Lauran
Mirela Coman

Abstract

The paper presents an introduction to the Ant Colony Optimisation (ACO) algorithm and methods for solving the Travelling Salesman Problem (TSP). Documenting, understanding and knowledge of concepts regarding the emergent behavior and intelligence swarms optimization, easily led on solving the Travelling Salesman Problem using a computational program, such as Mathematics Wolfram via Creative Demostration Projects (*.cdf) module.

The proposed application runs for a different number of ants, a different number of ants, a different number of leaders (elite ants), and a different pheromone evaporation index. As a result it can be stated that the execution time of the algorithm to solve the TSP is direct and strictly proportional to the number of ants, cities and elite ants considered, the increase of the execution time increasing significantly with the increase of the variables.

Keywords:
Ant colony optimisation, TSP, Wolfram Mathematica apps, analytical feedback.

Article Details

How to Cite
Cioruța, B.-V., Lauran, A., & Coman, M. (2020). Some Analytical Considerations Regarding the Traveling Salesman Problem Solved with Wolfram Mathematica Applications. Asian Journal of Advanced Research and Reports, 12(1), 68-77. https://doi.org/10.9734/ajarr/2020/v12i130281
Section
Original Research Article

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