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.


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