## Quasi-Monte Carlo random search is useful in nondifferentiable optimization. Borrowing ideas of population evolution from genetic algorithms, we introduce an adaptive random search in quasi-Monte Carlo methods (AQMC) for global optimization. Adaptive technique is used such that local search can
โฆ LIBER โฆ
Pure adaptive search in monte carlo optimization
โ Scribed by Nitin R. Patel; Robert L. Smith; Zelda B. Zabinsky
- Publisher
- Springer-Verlag
- Year
- 1989
- Tongue
- English
- Weight
- 554 KB
- Volume
- 43
- Category
- Article
- ISSN
- 0025-5610
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
Adaptive random search in Quasi-Monte Ca
โ
Guiyuan Lei
๐
Article
๐
2002
๐
Elsevier Science
๐
English
โ 569 KB
Pure adaptive search in global optimizat
โ
Zelda B. Zabinsky; Robert L. Smith
๐
Article
๐
1992
๐
Springer-Verlag
๐
English
โ 772 KB
Adaptive optimization of the Monte-Carlo
โ
A. N. Nakonechnyi; V. D. Shpak
๐
Article
๐
1994
๐
Springer US
๐
English
โ 346 KB
Pure adaptive search for finite global o
โ
Z. B. Zabinsky; G. R. Wood; M. A. Steel; W. P. Baritompa
๐
Article
๐
1995
๐
Springer-Verlag
๐
English
โ 363 KB
Monte Carlo tree search in Kriegspiel
โ
Paolo Ciancarini; Gian Piero Favini
๐
Article
๐
2010
๐
Elsevier Science
๐
English
โ 741 KB
A Feedback Algorithm for Determining Sea
โ
Chris Morey; John Scales; Erik S. Van Vleck
๐
Article
๐
1998
๐
Elsevier Science
๐
English
โ 242 KB
Monte Carlo methods have become popular for obtaining solutions to global optimization problems. One such Monte Carlo optimization technique is simulated annealing (SA). Typically in SA the parameters of the search are determined a priori. Using an aggregated, or lumped, version of SA's associated M