Generalized Simulated Annealing for Function Optimization

Optimal decomposition of probabilistic networks by simulated annealing

“…Although the annealing algorithm has been successfully applied to provide highquality approximate solutions to many NP-complete problems (Bohachevsky et al, 1986;Geman and Geman, 1984;Lundy, 1985;Thomas, 1986), convergence of the algorithm in less than exponential time cannot be guaranteed for general problems (Lundy and Mees, 1986). The purpose of this paper, however, has been to investigate the applicability of the algorithm under bounded resources.…”

A stochastic probing algorithm for global optimization

“…1.3. GENERALIZED SIMULATED ANNEALING Bohachevsky, Johnson and Stein (1986) (hereafter, BJS) considered a modification of the standard algorithm for continuous ~. The key to their suggestion is to modify the move selecting distribution in an attempt to accelerate the convergence to the minimum.…”

“…Some useful references are B61isle et al (1990), Pronzato et al (1984), Rinnooy Kan et al (1985, and van Laarhoven and Aarts (1987). Of special interest to statisticians, Bohachevsky et al (1986) and Haines (1987) have applied annealing to experimental design and Geman and Geman (1984) and Geman and McClure (1985) employed simulated annealing for Bayesian image restoration.…”

“…The method is related to simulated annealing, especially the "generalized" approach of Bohachevsky et al (1986). The method attempts to incorporate problem specific information to direct the search.…”

“…Bohachevsky et al (1986) considered three functions on [-1, 1] 2 to study the performance of their generalized simulated annealing algorithm. These functions arel q~l(x, y) = ax z + by 2 -c cos(ax) -d cos(yy) + c + d (3.1)th2(x , y) = ax 2 + by z -c eos(ax) cos(yy) + c (3.2)4~3(x, y) = ax 2 + by 2 -c cos(ax + rY) + c (3.3)…”