Solving Travelling Salesman Problem Using Heart Algorithm

Abdolreza Hatamlou
Additional contact information
Abdolreza Hatamlou: Department of Computer Science, Khoy Branch, Islamic Azad University, Khoy, Iran

International Journal of Applied Evolutionary Computation (IJAEC), 2017, vol. 8, issue 4, 32-42

Abstract: Solving hard problems like the Travelling Salesman Problem (TSP) is a major challenge faced by analysts even though many techniques are available. The main goal of TSP is that a number of cities should be visited by a salesman and return to the starting city along a number of possible shortest paths. TSP is although looking a simple problem, but it is an important problem of the classical optimization problems that are difficult to solve conventionally. It has been proved that solving TSP by the conventional approaches in a reasonable time is not possible. So, the only feasible option left is to use heuristic algorithms. In this article, we apply and investigate a new heuristic approach called Heart algorithm to solve Travelling Salesman Problem. It simulates the heart action and circulatory system procedure in the human beings for searching the problem space. The Heart algorithm has the advantages of strong robustness, fast convergence, fewer setting parameters and simplicity. The results of the Heart algorithm on several standard TSP instances is compared with the results of the PSO and ACO algorithms and show that the Heart algorithm performs well in finding the shortest distance within the minimum span of time.

Date: 2017
References: Add references at CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 018/IJAEC.2017100103 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jaec00:v:8:y:2017:i:4:p:32-42

Access Statistics for this article

International Journal of Applied Evolutionary Computation (IJAEC) is currently edited by Sukhpal Singh Gill

More articles in International Journal of Applied Evolutionary Computation (IJAEC) from IGI Global
Bibliographic data for series maintained by Journal Editor ().