On the convergence of parallel simulated annealing

Christian Meise

Stochastic Processes and their Applications, 1998, vol. 76, issue 1, 99-115

Abstract: We consider a parallel simulated annealing algorithm that is closely related to the so-called parallel chain algorithm. Periodically a new state from states is chosen as the initial state for simulated annealing Markov chains running independent of each other. We use selection strategies such as best-wins or worst-wins and show that the algorithm in the case of best-wins does not in general converge to the set of global minima. Indeed the period length and the number have to be large enough. In the case of worst-wins the convergence result is true. The phenomenon of the superiority of worst-wins over best-wins already occurs in finite-time simulations.

Keywords: Simulated; annealing; Nonhomogeneous; Markov; processes (search for similar items in EconPapers)
Date: 1998
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304-4149(98)00011-8
Full text for ScienceDirect subscribers only

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:spapps:v:76:y:1998:i:1:p:99-115

Ordering information: This journal article can be ordered from
http://http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

Access Statistics for this article

Stochastic Processes and their Applications is currently edited by T. Mikosch

More articles in Stochastic Processes and their Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().