Article ID: | iaor20083392 |
Country: | United Kingdom |
Volume: | 39 |
Issue: | 6 |
Start Page Number: | 701 |
End Page Number: | 714 |
Publication Date: | Sep 2007 |
Journal: | Engineering Optimization |
Authors: | Ahmed Mohamed A. |
Keywords: | programming: probabilistic, simulation, markov processes |
A modification of the simulated annealing (SA) algorithm for solving discrete stochastic optimization problems where the objective function is stochastic and can be evaluated only through Monte Carlo simulation is proposed. In this modification, the Metropolis criterion depends on whether the objective function values indicate a statistically significant difference at each iteration. The differences between objective function values are considered to be statistically significant based on confidence intervals associated with these values. Unlike the original SA, the proposed method uses a constant temperature. It is shown that the configuration that has been visited most often in the first