Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.13091/531
Title: A Hierarchical Approach Based on ACO and PSO by Neighborhood Operators for TSPs Solution
Authors: Eldem, Hüseyin
Ülker, Erkan
Keywords: Ant Colony Optimization
Swarm Intelligence
Neighborhood Operators
Traveling Salesman Problem
Metaheuristic
Particle Swarm Optimization
Hierarchical Approach
Traveling Salesman Problem
Optimization Algorithm
Search Algorithm
Particle Swarm
Publisher: WORLD SCIENTIFIC PUBL CO PTE LTD
Abstract: It is known that some of the algorithms in optimization field have originated from inspiration from animal behaviors in nature. Natural phenomena such as searching behavior of ants for food in a collective way, movements of birds and fish groups as swarms provided the inspiration for solutions of optimization problems. Traveling Salesman Problem (TSP), a classical problem of combinatorial optimization, has implementations in planning, scheduling and various scientific and engineering fields. Ant colony optimization (ACO) and Particle swarm optimization (PSO) techniques have been commonly used for TSP solutions. The aim of this paper is to propose a new hierarchical ACO- and PSO-based method for TSP solutions. Enhancing neighboring operators were used to achieve better results by hierarchical method. The performance of the proposed system was tested in experiments for selected TSPLIB benchmarks. It was shown that usage of ACO and PSO methods in hierarchical structure with neighboring operators resulted in better results than standard algorithms of ACO and PSO and hierarchical methods in literature.
URI: https://doi.org/10.1142/S0218001420590399
https://hdl.handle.net/20.500.13091/531
ISSN: 0218-0014
1793-6381
Appears in Collections:Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections

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