The application of ant colony optimization in the solution of 3D traveling salesman problem on a sphere
Küçük Resim Yok
Tarih
2017
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
ELSEVIER - DIVISION REED ELSEVIER INDIA PVT LTD
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Traveling Salesman Problem (TSP) is a problem in combinatorial optimization that should be solved by a salesperson who has to travel all cities at the minimum cost (minimum route) and return to the starting city (node). Todays, to resolve the minimum cost of this problem, many optimization algorithms have been used. The major ones are these metaheuristic algorithms. In this study, one of the metaheuristic methods, Ant Colony Optimization (ACO) method (Max-Min Ant System - MMAS), was used to solve the Non-Euclidean TSP, which consisted of sets of different count points coincidentally located on the surface of a sphere. In this study seven point sets were used which have different point count. The performance of the MMAS method solving Non-Euclidean TSP problem was demonstrated by different experiments. Also, the results produced by ACO are compared with Discrete Cuckoo Search Algorithm (DCS) and Genetic Algorithm (GA) that are in the literature. The experiments for TSP on a sphere, show that ACO's average results were better than the GA's average results and also best results of ACO successful than the DCS. (C) 2017 Karabuk University. Publishing services by Elsevier B.V. This is an open access article under the CC BY-NC-ND license
Açıklama
Anahtar Kelimeler
Ant colony optimization, Metaheuristic, Spherical geometry, Max-Min Ant System, nonEuclidean TSP
Kaynak
ENGINEERING SCIENCE AND TECHNOLOGY-AN INTERNATIONAL JOURNAL-JESTECH
WoS Q Değeri
N/A
Scopus Q Değeri
Q1
Cilt
20
Sayı
4
