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Comparision of ant colony and genetic algorithms for the solution of travel salesman problem
(Altınbaş Üniversitesi, 2018) Alashheb, Waled Milad Abulsasem; Duru, Adil Deniz; Uçan, Osman Nuri; Bayat, Oğuz
The Theory of computational complexity is an essential branch of study in the science of theoretical computing and mathematics. The resolution of Polynomial and Non Polynomial problems is one of the main problems that have open solutions, for which no famous efficient algorithm exist. The Problem of Traveling Salesman (TSP) is an example of these problems. Such a problem include, a count of specified cities must be visited by a traveling salesman where both start and end points will be the same city and getting a tour of all cities so that the complete distance or time is minimized will be the aim. The application of Optimization algorithms is one of the famous methods of the solution regarding to the TSP. These algorithms usually simulate the occurring phenomena in nature. Currently there exist several of such algorithms; for example, Genetic Algorithm (GA) and Optimization of Ant Colony (ACO). This paper aimed to compare two approaches, GA and ACO for solution of TSP. The results obtained from our experiments showed that the ACO is better than GA since it requires less execution time for solving the same problem.