POSSIBILISTIC PROGRAMMING DECISION PROBLEMS WITH PRIOR GOALS

In this paper, an upper level decision problem is formed by a set of possibilistic constraint conditions with possibilistic ideal goals of decision variables given by a decision maker. Possibilistic programming decision problems are proposed to obtain the possibilistic decision which approaches the possibilistic ideal goals as much as possible subject to possibilistic constraints. Two possibility distributions are considered for re-fleeting the inherent uncertainty in the decision problem. The possibilistic programming problems can be converted into conventional quadratic programming problems. The analysis results show that the proposed methods are effective for upper level decision problems under uncertainty which are extensively encountered in business and economics.