An Efficient Simulation Based Optimization Algorithm, For Stochastic Engineering Problems
Talal Madi Alkhamis
Dept. of Statistics and Operations Research, Kuwait University
P. O. Box 5969, Safat, Kuwait
In this paper we propose an approach based on Simulated Annealing (SA) algorithm to solve a special class of discrete stochastic engineering optimization problems where the objective function can be represented as the probability involving a performance event of a stochastic system. Similar to the original SA algorithm, the proposed approach has the hill climbing feature to escape the trap of local optima. However, unlike the original SA, our method uses constant temperature rather than decreasing temperature. Computational results are given to demonstrate the performance of the proposed variant of SA algorithm.