Capital rationing under risk: a chance constrained approach using uniformly distributed cash flows and available budgets

This paper presents pure capital rationing and selection of the best capital project mix when cash flows and available budgets are uniformly distributed random variables. Chance-constrained programming is used by approximating uniformly distributed random variables into normally distributed ones. Thus, a methodology is proposed to handle uniformly distributed random variables in capital rationing. The accuracy of the results is checked using the Monte-Carlo simulation technique. A literature review on the inclusion of risk into capital investment decisions using chance-constrained programming is also provided.