Improving the Hopfield model performance when applied to the traveling salesman problem-Reference-Cited by-同舟云学术

Improving the Hopfield model performance when applied to the traveling salesman problem

Published:2016-01-29 Issue:14 Volume:21 Page:3891-3905
ISSN:1432-7643
Container-title:Soft Computing
language:en
Short-container-title:Soft Comput

Author:

García Lucas^ORCID,Talaván Pedro M.,Yáñez Javier^ORCID

Funder

Government of Spain

Local Government of Madrid

Publisher

Springer Science and Business Media LLC

Subject

Geometry and Topology,Theoretical Computer Science,Software

Link

http://link.springer.com/article/10.1007/s00500-016-2039-8/fulltext.html

Reference21 articles.

1. Di Marco M, Forti M, Grazzini M, Pancioni L (2014) Necessary and sufficient condition for multistability of neural networks evolving on a closed hypercube. Neural Netw 54:38–48

2. Hopfield JJ (1984) Neurons with graded response have collective computational properties like those of two-state neurons. Proc Natl Acad Sci 81(10):3088–3092

3. Hopfield JJ, Tank DW (1985) “Neural” computation of decisions in optimization problems. Biol Cybern 52(3):141–152

4. Jolai F, Ghanbari A (2010) Integrating data transformation techniques with Hopfield neural networks for solving travelling salesman problem. Expert Syst Appl 37(7):5331–5335

5. Lawler EL (1985) The traveling salesman problem: a guided tour of combinatorial optimization. In: Wiley-Interscience series in discrete mathematics. Wiley, New York

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