Large Scale Traveling Salesman Problem Via Neural Network Divide and Conquer
Abstract
Among the early motivations for research in neural networks were works suggesting that they would show promise for combinatorial optimization problems such as the Traveling Salesman Problem. These hopes appeared to be disappointed by over a decade of disappointing results, due to scaling problems. However, these problems can be overcome, by application of divide-and-conquer strategies. Our results demonstrate that neural networks are capable of solving problems in the quarter-million city, range, with reasonable computational costs. Tour quality for this size problem remains poor, but the use of standard crossover removal algorithms should bring quality into an acceptable range for many applications.
Recommended Citation
S. Mulder and D. C. Wunsch, "Large Scale Traveling Salesman Problem Via Neural Network Divide and Conquer," Proceedings of the 9th International Conference on Neural Information Processing (ICONIP'02), vol. 2, pp. 533 - 536, Institute of Electrical and Electronics Engineers (IEEE), Jan 2002.
The definitive version is available at https://doi.org/10.1109/ICONIP.2002.1198112
Meeting Name
9th International Conference on Neural Information Processing (ICONIP'02) (2002: Nov. 18-22, Orchid Country Club, Singapore)
Department(s)
Electrical and Computer Engineering
International Standard Book Number (ISBN)
0009810475241
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2002 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Jan 2002
