Decision making in engineering and business: a cost-effective approach

A critical issue in all real life decision-making problems, is the effective estimation of the pertinent data. Often data are difficult to estimate with accuracy, or too dynamic to allow for a timely estimation. This is the case with most of the environmental, resource management, maintenance, economic, agricultural, and manufacturing problems, especially in the United States. If the input data are not correct, then the decision making process may cause a problem more severe than the one which it intended to solve. In this paper we propose an approach for a cost-effective estimation of the pertinent data. This approach is based on a sequence of successive sensitivity analyses