Abstract
In this paper, a possibilistic linear program is formulated when a measurable multiattribute value function is given. The possibilistic linear program in this paper is an unconstrained linear program with several objective functions whose coefficients are represented by possibility distributions. A possibility measure and a necessity measure are derived from a possibility distribution. Using fuzzy integrals of the measurable multiattribute value function with respect to the possibility measure and the necessity measure, the possible value and the necessary value are defined respectively. In an analogy of the expected utility, the principles of maximizing the possible value and the necessary value are considered as decision procedures under a possibility distribution. The possibilistic linear program is formulated based on these decision procedures and reduced to a nonlinear program. A solution method using linear programming technique is proposed. INFORMS Journal on Computing, ISSN 1091-9856, was published as ORSA Journal on Computing from 1989 to 1995 under ISSN 0899-1499.
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