LIQUIDITY MANAGEMENT WITH FUZZY QUALITATIVE CONSTRAINTS

The treasurer of a bank must balance liquidity flows every day in an e nvironment in which some future interest rates and transactions are kn own precisely, but some are uncertain. Decision support systems based on traditional mathematical programming approach find the optimal plan with respect to precise quantitative constraints provided by the user ; we here suggest a procedure by which such systems can utilize probab ilistic and Fuzzy qualitative constraints (e.g. ''the treasury might h ave to cover a small deficit next Friday''). Each qualitative judgemen t is formalized by a discrete possibility distribution, which is conve rted to a discrete probability distribution; in this form the problem can be solved by the simple recourse method. Unexpected surpluses/defi cits due to an uncertain future balance are evaluated in the objective function: by varying the evaluation coefficients along a scale from p essimistic to optimistic, we can obtain several solutions each adapted to a different risk policy.