Article ID: | iaor20043546 |
Country: | United Kingdom |
Volume: | 31 |
Issue: | 7 |
Start Page Number: | 1135 |
End Page Number: | 1145 |
Publication Date: | Jun 2004 |
Journal: | Computers and Operations Research |
Authors: | Huang Yeu-Shiang |
Keywords: | decision, artificial intelligence: decision support |
Generally, the successive failure times of repairable systems can become smaller (an indication of deterioration). Therefore, the decision of whether to overhaul or discard the system after some period of time is of fundamental importance. However, such a decision involves many uncertainties, such as the initial status of the system, the degree of deterioration, repair cost, and accident cost, etc., which are important factors and need to be evaluated carefully. The paper reviews several plausible approaches for dealing with such problems and develops a possible structural design of decision support systems by considering the sensitivity analysis as well as the optimal prior and posterior decisions. The proposed design of decision support systems facilitates the effective use of the computing capability of computers and provides a systematic way to integrate the expert's opinions and the sampling information which will furnish decision makers with valuable support for quality decision-making.