Annealing is the process of slowly cooling a physical system in order to obtain states with globally minimum energy. By simulating such a process, near-globally-minimum-cost solutions can be found for very large optimization problems. The author reviews the basic theory of simulated annealing and surveys its recent applications and the theoretical approaches that have been used to study the technique. The applications include image restoration, combinatorial optimization (e. g. VLSI routing and placement), code design for communication systems and certain aspects of artificial intelligence. The theoretical tools for analysis include the theory of nonstationary Markov chains, statistical physics analysis techniques, large deviation theory and singular perturbation theory.
|Number of pages
|Proceedings of the IEEE Conference on Decision and Control
|Published - 1985
ASJC Scopus subject areas
- Control and Systems Engineering
- Modeling and Simulation
- Control and Optimization