Parallelized neural network system for solving Euclidean traveling salesman problem

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Avşar, Bihter and Esmaeili Aliabadi, Danial (2015) Parallelized neural network system for solving Euclidean traveling salesman problem. Applied Soft Computing, 34 . pp. 862-873. ISSN 1568-4946 (Print) 1872-9681 (Online)

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Official URL: http://dx.doi.org/10.1016/j.asoc.2015.06.011


We investigate a parallelized divide-and-conquer approach based on a self-organizing map (SOM) in order to solve the Euclidean Traveling Salesman Problem (TSP). Our approach consists of dividing cities into municipalities, evolving the most appropriate solution from each municipality so as to find the best overall solution and, finally, joining neighborhood municipalities by using a blend operator to identify the final solution. We evaluate the performance of parallelized approach over standard TSP test problems (TSPLIB) to show that our approach gives a better answer in terms of quality and time rather than the sequential evolutionary SOM.

Item Type:Article
Uncontrolled Keywords:Euclidean traveling salesman problem; Artificial neural network; Parallelization; Self-organized map; TSPLIB
Subjects:Q Science > QA Mathematics > QA440 Geometry. Trigonometry. Topology
Q Science > QA Mathematics > QA076 Computer software
ID Code:31174
Deposited By:Danial Esmaeili Aliabadi
Deposited On:26 Apr 2017 11:34
Last Modified:26 Apr 2017 11:34

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