Incorporating Decision Maker Research Articles

Decision criteria in dual response

While a considerable body of research has investigated the dual response problem, there is a need to reflect decision maker preferences in the simultaneous optimization of the response functions. In this paper, we present a mathematically rigorous approach for incorporating decision maker preferences. By interpreting the Lagrangian as a value function and the Lagrange multiplier as a preference ratio, candidate solutions are explored that reflect decision maker preferences. We consider the dual response approach to the simultaneous maximization of two responses modelled as quadratic forms. A function relating the responses and the value of the Lagrange multiplier is derived, and appropriate restrictions for the multiplier are discussed. We present the approach in algorithmic form and provide an example that demonstrates the application of the method.

A Most Probable Point-Based Method for Efficient Uncertainty Analysis

Abstract Uncertainty is inevitable at every stage of life cycle development of a product. To make use of probabilistic information and to make reliable decisions by incorporating decision maker's risk attitude, methods for propagating the effect of uncertainty are therefore needed. When designing complex systems, the efficiency of methods for uncertainty propagation becomes critical. In this paper, a most probable point (MPP)-based uncertainty analysis (MPPUA) method is proposed. The concept of the MPP is utilized to generate the cumulative distribution function (CDF) of a system output by evaluating probability estimates at a serial of limit states across a range of output performance. To improve the efficiency of locating the MPP, a novel MPP search algorithm is presented that employs a new search algorithm and a search strategy. A mathematical example and an engine design problem are used to verify the effectiveness of the proposed method. The proposed MPPUA method will serve as a useful tool for propa...

A Most Probable Point-Based Method for Efficient Uncertainty Analysis

Abstract Uncertainty is inevitable at every stage of life cycle development of a product. To make use of probabilistic information and to make reliable decisions by incorporating decision maker's risk attitude, methods for propagating the effect of uncertainty are therefore needed. When designing complex systems, the efficiency of methods for uncertainty propagation becomes critical. In this paper, a most probable point (MPP)-based uncertainty analysis (MPPUA) method is proposed. The concept of the MPP is utilized to generate the cumulative distribution function (CDF) of a system output by evaluating probability estimates at a serial of limit states across a range of output performance. To improve the efficiency of locating the MPP, a novel MPP search algorithm is presented that employs a new search algorithm and a search strategy. A mathematical example and an engine design problem are used to verify the effectiveness of the proposed method. The proposed MPPUA method will serve as a useful tool for propagating the effect of uncertainty when making decisions under uncertainty.

A comparative analysis of DEA as a discrete alternative multiple criteria decision tool

The application of Data Envelopment Analysis (DEA) as a discrete alternative multiple criteria decision making (MCDM) tool has been gaining more attention in the literature. In this literature, DEA has been applied as an MCDM tool and compared analytically to other MCDM models and their structures, especially those that are based on multiple objective linear programming approaches. In this paper, we provide an empirical evaluation of various DEA ranking approaches and MCDM techniques, which include outranking and multiattribute utility techniques, using case study information. A solid waste management system case study that has been published by Hokkanen and Salminen (1997a) provide the data and results for this comparison. The results of this study show that incorporating decision maker value judgments into the DEA approaches provided comparable results to those found by the `traditional' MCDM approaches. The DEA approaches seem to be advantageous to users by requiring less information from decision makers and analysts, and providing ranked alternative valuations that may be useful for some decision makers.

Power Transition and Conflict Initiation

Most theories of war and lesser forms of international conflict rest on assumptions of rational choice. Moreover, many of these explanations explicitly incorporate decision maker estimates of relative power among competitors. However, a major theory of great power war-power transition theory-postulates initiation by the weaker contender. This study demonstrates that among the strongest states an interactive relationship exists between the static power balance, differential growth rates in capabilities, and conflict initiation: initiation patterns are associated with changes in a state's relative military/economic power and power potential. The findings are consistent with the inherent logic of power transition theory and are consonant with an assumption of rational calculation in decisions involving conflict initiation. The results may be interpreted as reinforcing the realist contention that a shifting power balance is of critical significance among the causes of war and peace.