An Integrated Self-Organizing Map for the Traveling Salesman Problem

Hui-Dong JIN, Kwong-Sak LEUNG, Man-Leung WONG

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

8 Citations (Scopus)


As a representative combinatorial optimization problem, the Traveling Salesman Problem (TSP) has attracted extensive research. In this paper, we develop a new Self-Organizing Map (SOM) network for the TSP and call it the Integrated SOM (ISOM) network. Its learning rule embodies the effective mechanisms of three typical learning rules. In its single learning activity, the excited neuron first is dragged close to the input city, and then is expanded towards the convex-hull of the TSP, and finally, it is drawn close to the middle point of its two neighbor neurons. The elaborate cooperation among these three learning mechanisms is evolved by a genetic algorithm. The simulation results show that the finally established ISOM can generate more promising solutions, with similar computation time, than other neural networks like the SOM network, the Expanded SOM, and the Convex Elastic Net.
Original languageEnglish
Title of host publicationAdvances in Neural Networks and Applications
Publication statusPublished - 2001
Externally publishedYes
EventAdvances in Neural Networks and Applications - Spain, Spain
Duration: 1 Jan 20011 Jan 2001


ConferenceAdvances in Neural Networks and Applications
OtherWorld Scientific and Engineering Society

Bibliographical note

This research was partially supported by Hong Kong RGC CERG Grant CUHK 4161/97E.

Scopus: 0344942765


Dive into the research topics of 'An Integrated Self-Organizing Map for the Traveling Salesman Problem'. Together they form a unique fingerprint.

Cite this