SIMULATED ANNEALING, SA
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Abstract:
For NP-hard optimization problems, the use of exact algorithms for the evaluation of the optimal solution is computationally intensive requiring an effort that increases exponentially with the size of the problem. In practice, exact algorithms are used for solving only moderately sized problem instances. This results in the development of heuristic optimization techniques which provide good quality solutions in a reasonable amount of computational time. One such popular technique is simulated annealing (SA) which has been widely applied in both discrete and continuous optimization problems ([1], [4]). SA is a stochastic search method modeled according to the physical annealing process which is found in the field of thermodynamics. Annealing refers to the process of a thermal system initially melting at high temperature and then cooling slowly by lowering the temperature until it reaches a stable state (ground state), in which the system has its lowest energy. S.
