The 2-opt behavior of the Hopfield Network applied to the TSP
| Autor: | Lucas García, Javier Yáñez, Pedro M. Talaván |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Informática
0209 industrial biotechnology Numerical Analysis Mathematical optimization 021103 operations research Artificial neural network Computer science Matemáticas Strategy and Management 0211 other engineering and technologies Computational intelligence 02 engineering and technology Management Science and Operations Research 2-opt Travelling salesman problem Hopfield network 020901 industrial engineering & automation Computational Theory and Mathematics Management of Technology and Innovation Modeling and Simulation Line (geometry) Attractor Statistics Probability and Uncertainty Heuristics |
| Zdroj: | E-Prints Complutense: Archivo Institucional de la UCM Universidad Complutense de Madrid E-Prints Complutense. Archivo Institucional de la UCM instname |
| Popis: | The Continuous Hopfield Network (CHN) became one of the major breakthroughs in the come back of Neural Networks in the mid 80s, as it could be used to solve combinatorial optimization problems such as the Traveling Salesman Problem. Once researchers provided a mechanism, not based in trial-and-error, to guarantee the feasibility of the CHN, the quality of the solution was inferior to the ones provided by other heuristics. The next natural step is to study the behavior of the CHN as an optimizer, in order to improve its performance. With this regard, this paper analyzes the attractor basins of the CHN and establishes the mathematical foundations that guarantee the behavior of the network as a 2-opt; with the aim to open a new research line in which the CHN may be used, given the appropriate parameter setting, to solve a k-opt, which would make the network highly competitive. The analysis of the attraction basins of the CHN and its interpretation as a 2-opt is the subject of this article. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|