Sonia Cafieri, Jon Lee, et al.
Journal of Global Optimization
Simulated annealing is a stochastic algorithm for solving discrete optimization problems, such as the traveling salesman problem and circuit placement. To reduce execution time, researchers have parallelized simulated annealing. Serial-like algorithms identically maintain the properties of sequential algorithms. Altered generation algorithms modify state generation to reduce communication, but retain accurate cost calculations. Asynchronous algorithms reduce communication further by calculating cost with outdated information. Experiments suggest that asynchronous simulated annealing can obtain greater speedups than other techniques. It exhibits the properties of cooperative phenomena: processors asynchronously exchange information to bring the system toward a global minimum. This paper provides a comprehensive, taxonomic survey of parallel simulated annealing techniques, highlighting their performance and applicability. © 1990.
Sonia Cafieri, Jon Lee, et al.
Journal of Global Optimization
Ligang Lu, Jack L. Kouloheris
IS&T/SPIE Electronic Imaging 2002
A.R. Conn, Nick Gould, et al.
Mathematics of Computation
Harpreet S. Sawhney
IS&T/SPIE Electronic Imaging 1994