Modern socio-political-economic problems often represent situations in which the traditional numerical problem models fall far short of being adequate for determining formal solutions. The basic reason for this inadequacy is the fact that the objective functions in such problems contain abstract criteria. It, therefore, is difficult, if not impossible, to determine how much one alternative in the problem is preferred to another alternative. When such information is not available in a problem, a numerical model will serve to fabricate this information and, therefore, reduce the degree of isomorphism between the problem and the problem model. A linear program that uses a relations set as its objective function can maintain isomorphism. In such models, the single optimal solution may not be determinable. However, if the set of feasible solutions is ordered, the optimal solution can be determined. The same ordered approach also has some useful applications to games.

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The scientific exploration of the moon requires that a number of experiments be conducted for the purpose of investigating the many questions and hypotheses posed by nearly every discipline in the scientific community. The broad interest in this effort, the limitations of time and resources for conducting the program, and the complex engineering constraints imposed by the logistics system justify the development of an effective method of making optimum selection of experiments according to the most meaningful criteria. The developed method provides a determination of alternate optimum solutions from which scientific authority may choose. Basic lunar scientific objectives, as determined by NASA interdisciplinary panels, serve as inputs to the system. The relative worth of each objective according to scientific merit is determined by a stratified, intradisciplinary sample of the scientific community using a modified majority-rule technique. The experiments are then ordered according to their contribution to the ordered objectives. A subjective programming method provides alternate payload choices that optimize the scientific merit of the experiments within the engineering constraints of a lunar IMjdoad. An example is presented that simulates the use of an algorithm for sdecting an optimum experiment pajdoad.

The intent of this paper is to present a specific methodology for organizational diagnosis, which in order to be successful, requires that an interventionist as a third-party facilitator attend to many very specific (though sometimes subtle) process aspects. The traditional techniques used for organizational diagnosis-questionnaires, interviews, and participant observationare criticized as being content-influential. The process-oriented methodology presented involves the interventionist with the client in designing groups that represent four different constituencies of a particular organization unit. The initial diagnosis and the initial intervention is achieved by conducting a problem diagnosis workshop. Pragmatic aspects concerning an effective diagnostic intervention have been learned through extensive research experience, some of which the authors report.

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