The primary objective of this paper is to develop and suggest multi-objective criteria to the problem of capital rationing by making use of the potentials of stochastic goal programming, to deal with the proposed problem. Here, the concept of carry forward of cash for the stochastic environment has been discussed. Most of the literature on capital rationing decisions in the past has been woven around the assumption of certainty and single objective, whereas the reality is seldom so. One can not simply assume the cash flows to be certain. But as soon as these assumptions are violated one is apparently in a dilemma in the processes of decisionmaking. The proposed model would provide useful solution under those circumstances when the event cash flows follow beta distribution and the period cash flows obey the properties of normal distribution.

Optimum capital budget is nothing but the availability of funds to invest in all moneymaking projects so as to maximize the net present value. Capital rationing occurs when management places a constraint on the size of the firm’s capital budget during a particular period. In other words, a situation in which a firm limits its capital expenditures to less than the amount required for funding the optimal capital budget.

Most of the literature on capital budgeting/rationing decision under risk and uncertainty has mainly followed three approaches, namely, Simplistic Approach, Portfolio Theory Approach and Mathematical Programming Approach. Simplistic and portfolio approaches suffer from certain limitations such as considering single objective function, failing to provide solution when there exits a problem of invisibilities in the investment projects, and not more than any one project can be included in the final program of choosing projects. In order to overcome these limitations mathematical programming approaches have been proposed.

Most of the literature on capital rationing decisions in the past has been woven around the assumption of certainty and single goal, since the assumption of certainty facilitates the analysis and decision making process to be straightforward. But once this assumption is relaxed we are apparently faced with great dilemma and decision-making process tends to collapse in mire confusion because in actual practice one rarely inhibits the land of complete certainty or postulation of single goal. Therefore, our intent in the present work is to suggest a multi-objective criterion to the problem of uncertainty by applying stochastic goal programming model, according to chance constraint technique.