This new form of multiattribute utility optimization is based on ordinal as opposed to cardinal utility and is defined from a corresponding integer programming model in operations research which (1) is solved for ordinal cost factors and (2) serves as the problem's theoretical starting point. It is suggested herein that one start with a mathematical formulation that if solved in an acceptable or — preferably — best manner would yield a satisfactory or possibly best solution to the problem. Then, that mathematical formulation and its solution technique defines the multiattribute utility problem and its solution at issue. This is the reverse of what is usually done; and as will be shown, doing this can be quite fruitful. The illustrative example concerns a mathematical 1 formulation based on operation research's assignment problem. As will be argued, the cost factors must be ordinal, which essentially corresponds to using ordinal utility; hence the technique will be framed in the realm of ordinal utility. The technique for solving the illustrative example's mathematical formulation is to achieve a premium mix of operations research solution properties. From this perspective, some sticky issues in multiattribute utility theory when the attributes involve the preferences of distinct persons are not included in the philosophical base for the multiattribute utility problem and its solution thusly defined. / Master of Arts