Nearest-neighbour heuristics in accelerated algorithms of optimisation problems
Simon C. Lin and
H.C. Hsueh
Physica A: Statistical Mechanics and its Applications, 1994, vol. 203, issue 3, 369-380
Abstract:
A scalable linear algorithm of simulated annealing (SA) was proposed by Lin et al. that is capable of achieving a near optimal solution for the travelling saleman problem in a controllable way. Since the linearity is based on the hybrid mechanism that combines SA heuristics with the scaling relation of acceptance ratio in the low temperature, other conventional heuristics in optimisation problems ought to be tried. The nearest-neighbour (NN) heuristics is thus studied, and one finds that the quenched configuration of NN's could be resurrected back to SA path by the hybrid mechanism. It is also verified that the same scalable linear algorithm of Lin's may continue to apply with exactly the same set of parameters.
Date: 1994
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/0378437194900051
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:203:y:1994:i:3:p:369-380
DOI: 10.1016/0378-4371(94)90005-1
Access Statistics for this article
Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis
More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().