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Optimization Based on Simulation of Ants Colony

  • Mihailo JovanovićEmail author
  • Ermin Husak
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 76)

Abstract

Natural processes optimize life on earth for thousands of years, so people are inspired by many problem-solving techniques in nature. Metaheuristics inspired by natural processes and systems have become a very active field of research in recent years. One of the most popular methods is Ant Colony Optimization (ACO). In this paper is considered the application of Ant Colony Optimization in the case of the Traveling Salesman Problem (TSP). Different cases, with a different number of ants (population size) with a different number of iteration using software simulation, are considered. It is shown that Roulette Wheel Selection has some impact on the speed of the result. On the other hand, with more ants in each iteration, we get more constructed solutions, which increases the probability of finding a better solution.

Keywords

Ant Colony Optimization ACO Software Traveling Salesman Problem – TSP 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Faculty of Management Herceg NoviHerceg NoviMontenegro
  2. 2.Technical FacultyUniversity of BihaćBihaćBosnia and Herzegovina

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