Simulated annealing is a probabilistic method proposed in Kirkpatrick, Gelett and Vecchi
(1983) and Cerny (1985) for finding the global minimum of a cost function that may possess …

Simulated annealing is a general approach for approximately solving large combinatorial
optimization problems. The algorithm is based on an intriguing combination of ideas from at …

Much work has been published on the theoretical aspects of simulated annealing. This
paper provides a brief overview of this theory and provides an introduction to the practical …

Simulated annealing (SA) presents an optimization technique with several striking positive
and negative features. Perhaps its most salient feature, statistically promising to deliver an …

The book deals in depth with an optimization algorithm called'simulated annealing'.
Applications to various fields are discussed. The review is written from a mathematician's …

A Monte Carlo optimization technique called “simulated annealing” is a descent algorithm
modified by random ascent moves in order to escape local minima which are not global …

Simulated annealing algorithms are time inhomogeneous controlled Markov chains used to
search for the minima of energy functions defined on finite state spaces. The control …

Theoretical and computational aspects of simulated annealing Page 1 Theoretical and
computational aspects of simulated annealing Citation for published version (APA): van …

Simulated annealing is a randomized algorithm which has been proposed for finding
globally optimum least-cost configurations in large NP-complete problems with cost …

Adaptive simulated annealing (ASA) is a global optimization algorithm based on an
associated proof that the parameter space can be sampled much more efficiently than by …