Project selection and adjustment based on uncertain measure

This paper discusses a project selection and adjustment problem in the situation where some project parameters are given by experts’ estimates because of lack of historical data. Uncertain variables are used to describe these project parameters and the use of them is justified. Based on uncertain measure, a cost overrun risk which describes the average amount of investment outlay exceeding the available budget is proposed, and a new optimization model which simultaneously considers the selection of new projects and the adjustment of existing ones is developed. To solve the proposed problem, the deterministic equivalents of the model are provided and a genetic algorithm is offered. As an illustration, an example is also presented and discussed.