Optimal Replacement for Shock Processes.
TEXAS A AND M UNIV COLLEGE STATION DEPT OF INDUSTRIAL ENGINEERING
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The research performed under this grant successfully developed a method for determining an optimal state-age dependent replacement policy for a semi-Markov shock model. Comparisons between the method developed here and the standard policy iteration approach show a significant improvement in computer speed and memory requirements. Author
- Statistics and Probability