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ABSTRACTThis paper addresses two issues critical to the success of decision support systems in multiattribute/multicriteria decision‐making contexts. A relationship is established between normative (prescriptive) work in the area of multicriteria decision making and behavioral (descriptive) decision research involving choice strategies. A conceptual system architecture based on the state‐space approach to problem solving is presented. This architecture will enable decision makers to incorporate both prescriptive and descriptive strategies in the course of computer‐aided multiple alternative/attribute problem resolution.

In this note, we provide an easy-to-understand introduction to strength-of-preference measures in the context of deterministic multiattribute value assessments, focusing on what they are and why they matter. Though these issues are well understood by some decision analysts, we believe that many do not understand or appreciate the role of strength-of-preference assumptions when assessing or interpreting multiattribute value functions. The note is structured around an argument between the two authors that took place when reviewing applications of multiattribute value functions.

Radiation protection authorities have seen a potential for applying multiattribute risk analysis in nuclear emergency management and planning to deal with conflicting objectives, different parties involved, and uncertainties. This type of approach is expected to help in the following areas: to ensure that all relevant attributes are considered in decision making; to enhance communication between the concerned parties, including the public; and to provide a method for explicitly including risk analysis in the process. A multiattribute utility theory analysis was used to select a strategy for protecting the population after a simulated nuclear accident. The value‐focused approach and the use of a neutral facilitator were identified as being useful.

1. Guided Soul-Searching for Multi-Criterion Decisions -- 2. Interpersonal Comparison of Utilities -- 3. Group Decision Analysis -- 4. Externalizing the Parameters of Quasirational thought -- 5. Multivariate Selection of Students in a Racist Society: A Systematically Unfair Approach -- 6. A Multi-Objective Model for Planning Equal Employment Opportunities -- 7. Experiences in multiobjective management processes -- 8. The theory of the Displaced Ideal -- 9. The Surrogate Worth Trade-Off Method with Multiple Decision-Makers -- 10. An Interactive Multiple Objective Decision-Making Aid Using Nonlinear Goal Programming -- 11. Applications of Multiple Objectives to Water Resources Problems -- 12. On the Approximation of Solutions to Multiple Criteria Decision Making Problems -- 13. Why Multicriteria Decision Aid May Not Fit in with the Assessment of a Unique Criterion -- 14. Multiattribute Preference Functions of University Administrators -- 15. MCDM Bibliography 1975 -- 16. Multicriteria Simplex Method: A Fortran Routine.

Sponsored Report (for Acquisition Research Program) ; The current fiscal crisis has placed unprecedented pressure on public procurements. A major target of future public spending cuts is likely to be defense expenditures. Within the defense budget, the biggest and most immediate targets are likely to be the acquisition of new equipment, facilities, services, and supplies. Addressing the growing global challenge of affordability, this paper offers a new approach to government''s vendor selection decisions in major public procurements. In the absence of profits to guide public procurement decisions, the challenge that faces a government buyer is to select the vendor that delivers the best combination of desired non-price attributes at realistic funding levels. The governance mechanism proposed in this paper is a multiattribute first price, sealed bid procurement auction. It extends traditional price-only auctions to one in which competition takes place exclusively over bundles of desired non-price attributes. The first iteration of the model is a multiattribute auction in which a fixed budget constraint is specified. Next, the model is expanded to incorporate a range of possible budget levels. This expanded model reveals the benefits to the buyer of defining a procurement alternative (vendor bid proposal) in terms of its value to the buyer over a range of possible expenditures, rather than as a single point in budget-value space. This new approach leads to some interesting results. In particular, it suggests that in a fiscally constrained environment, the traditional approach of eliminating dominated alternatives could lead to sub-optimal decisions. The final extension of the model explicitly examines the buyer''s decision problem under budget uncertainty. ; Naval Postgraduate School Acquisition Research Program ; Approved for public release; distribution is unlimited.

Targets are used quite often as a management tool, and it has been argued that thinking in terms of targets may be more natural than thinking in terms of utilities. The standard expected-utility framework with a single attribute (such as money) and nondecreasing, bounded utility is equivalent to a target-oriented setting. A utility function, properly scaled, can be expressed as a cumulative distribution function (cdf) and related to the probability of meeting a target value. We consider whether the equivalence of the two approaches extends to the case of multiattribute utility. Our analysis shows that a multiattribute utility function cannot always be expressed in the form of a cumulative distribution function and, furthermore, cannot always be expressed in the form of a target-oriented utility function. However, in each case equivalence does hold for certain well-known classes of utility functions. In general, our results imply that although interpreting utility as a cdf and thinking about achieving targets works fine in the case of a single attribute, this approach should be used with caution in the multiattribute case, with cdf representations requiring more caution than target-oriented representations.

Each of us makes a number of decisions, from the less important to those with
far-reaching consequences. As members of different groups, we are also actors
of group decision making. In order to make a rational decision, a
choice-making procedure must satisfy a number of assumptions (conditions) of
rationality. In addition, when it comes to group decisions, those procedures
should also be ?fair.? However, it is not possible to define a procedure of
choice-making that would transform individual orders of alternatives based on
preferences of perfectly rational individuals into a single social order and
still meet conditions of rationality and ethics. The theory of deliberative
democracy appeared in response to the impossibility of Social Choice theory.
The basic assumption of deliberative democracy is that individuals adjust
their preferences taking into account interests of the community. They are
open for discussion with other group members and are willing to change their
attitudes in order to achieve common interests. Ideally, group members come
to an agreement during public discussion (deliberation). Still, this concept
cannot completely over?come all the difficulties posed by the theory of
social choice. Specifically, there is no solution for strategic and
manipulative behavior of individuals. Also, the concept of deliberative
democracy faces certain problems particular to this approach, such as, to
name but a few, problems with the establishment of equality of participants
in the debate and their motivation, as well as problems with the organization
of public hearings.

AbstractThe HOPE (Holistic Orthogonal Parameter Estimation) elicitation procedure assesses multiattribute utility functions via sample holistic judgments. Analyses of actual judgmental data are presented that support two simple assertions: (1) HOPE‐derived utilities are valid and (2) the resulting utility functions are useful for decision making.

This article describes the anti‐terrorism risk‐based decision aid (ARDA), a risk‐based decision‐making approach for prioritizing anti‐terrorism measures. The ARDA model was developed as part of a larger effort to assess investments for protecting U.S. Navy assets at risk and determine whether the most effective anti‐terrorism alternatives are being used to reduce the risk to the facilities and war‐fighting assets. With ARDA and some support from subject matter experts, we examine thousands of scenarios composed of 15 attack modes against 160 facility types on two installations and hundreds of portfolios of 22 mitigation alternatives. ARDA uses multiattribute utility theory to solve some of the commonly identified challenges in security risk analysis. This article describes the process and documents lessons learned from applying the ARDA model for this application.