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A method is presented for ranking multiattributed alternatives using a weighted-additive evaluation function with partial information about the weighting (scaling) constants, the method is applied to evaluate materials for use in nuclear waste containment. The paper derives conditions to determine whether a pair of alternatives can be ranked given the partial information about weighting constants, and presents an algorithm that partially rank-orders the complete set of alternatives based on the pairwise ranking information.

Global warming has profound consequences for the climate of the American Southwest and its overallocated water supplies. This paper uses simulation modeling and the principles of decision making under uncertainty to translate climate information into tools for vulnerability assessment and urban climate adaptation. A dynamic simulation model, WaterSim, is used to explore future water-shortage conditions in Phoenix. Results indicate that policy action will be needed to attain water sustainability in 2030, even without reductions in river flows caused by climate change. Challenging but feasible changes in lifestyle and slower rates of population growth would allow the region to avoid shortage conditions and achieve groundwater sustainability under all but the most dire climate scenarios. Changes in lifestyle involve more native desert landscaping and fewer pools in addition to slower growth and higher urban densities. There is not a single most likely or optimal future for Phoenix. Urban climate adaptation involves using science-based models to anticipate water shortage and manage climate risk.water sustainability | climate change | decision making under uncertainty | simulation modeling

This article reports a procedure developed to assist the U.S. Department of Energy in selecting a portfolio of solar energy applications experiments. The procedure has also been used in other government procurements and appears to be applicable in a variety of project funding processes. The technical quality of each proposed applications experiment was summarized through the use of multiple evaluation measures, or attributes. These were combined into a single index of the overall technical quality of an experiment through the use of a multiattribute utility function. Recently derived results in measurable value theory were applied to derive an index of the overall technical quality of a portfolio of experiments. Budgetary and programmatic issues were handled through the use of constraints. This approach allowed the portfolio selection problem to be formulated as an integer linear program. Details of the application are presented, including a discussion of the data requirements and assessment procedure used. The portfolio selection procedure was successfully applied, and variations of it have been successfully used in four other solar energy procurements.research and development: project selection, utility/preference: multiattribute, programming: integer, applications

This paper develops an approach based on performance targets to assess a preference function for a multiobjective decision under uncertainty. This approach yields preference functions that are strategically equivalent to conventional multiattribute utility functions, but the target-oriented approach is more natural for some classes of decisions. In some situations, the target-oriented preference conditions are analogous to reliability theory conditions for series or parallel failure modes in a system. In such cases, reinterpreting the conditions using reliability concepts can be useful in assessing the preference function. The target-oriented approach is also a generalization of common forms of goal programming. The approach has particular applicability for resource allocation decisions where the outcome of the decision is significantly determined by the actions of other stakeholders to the decision, such as new product development or decision making in a controversial regulated environment.