(1998) Efficient convexelastic net algorithm to solve the Euclideantraveling salesman problem. Systems, Man, and Cybernetics, Part B, IEEE Transactions on, 28.

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Abstract
This paper describes a hybrid algorithm that combines an adaptivetype neural network algorithm and a nondeterministic iterative algorithm to solve the Euclidean traveling salesman problem (ETSP). It begins with a brief introduction to the TSP and the ETSP. Then, it presents the proposed algorithm with its two major components: the convexelastic net (CEN) algorithm and the nondeterministic iterative improvement (NII) algorithm. These two algorithms are combined into the efficient convexelastic net (ECEN) algorithm. The CEN algorithm integrates the convexhull property and elastic net algorithm to generate an initial tour for the ETSP. The NII algorithm uses two rearrangement operators to improve the initial tour given by the CEN algorithm. The paper presents simulation results for two instances of ETSP: randomly generated tours and tours for wellknown problems in the literature. Experimental results are given to show that the proposed algorithm ran find the nearly optimal solution for the ETSP that outperform many similar algorithms reported in the literature. The paper concludes with the advantages of the new algorithm and possible extensions
Item Type:  Article 

Subjects:  Computer 
Department:  College of Computing and Mathematics > Information and Computer Science 
Depositing User:  Mr. Admin Admin 
Date Deposited:  24 Jun 2008 13:33 
Last Modified:  01 Nov 2019 14:05 
URI:  https://eprints.kfupm.edu.sa/id/eprint/14378 