Euclid: An Interactive Decision Support System with Applications

Euclid is a simple and yet sophisticated Interactive Decision Support System. Euclid uncovers some of the complexities inherent in the evaluation of strategic alternatives.Euclid is based on a simple concept of dividing decision criteria into: Maximizing (Opportunities/Strengths) and Minimizing (Threats/Weaknesses) . Euclid can be used in an interactive mode for‘‘goal seeking’’and‘‘what-if’’analysis.Decision makers often need a rational model like Euclid to help them manage this complex process and make informed decision

Influence of aggregation and measurement scale on ranking a compromise alternative in AHP

Analytic Hierarchy Process (AHP) is one of the most popular multi-attribute decision aid methods. However, within AHP, there are several competing preference measurement scales and aggregation techniques. In this paper, we compare these possibilities using a decision problem with an inherent trade-off between two criteria. A decision-maker has to choose among three alternatives: two extremes and one compromise. Six different measurement scales described previously in the literature and the new proposed logarithmic scale are considered for applying the additive and the multiplicative aggregation techniques. The results are compared with the standard consumer choice theory. We find that with the geometric and power scales a compromise is never selected when aggregation is additive and rarely when aggregation is multiplicative, while the logarithmic scale used with the multiplicative aggregation most often selects the compromise that is desirable by consumer choice theory.AHP, Multi-criteria Decision analysis

Does AHP help us make a choice? - An experimental evaluation

In this paper, we use experimental economics methods to test how well Analytic Hierarchy Process (AHP) fares as a choice support system in a real decision problem. AHP provides a ranking that we statistically compare with three additional rankings given by the subjects in the experiment: one at the beginning, one after providing AHP with the necessary pair-wise comparisons and one after learning the ranking provided by AHP. While the rankings vary widely across subjects, we observe that for each individual all four rankings are similar. Hence, subjects are consistent and AHP is, for the most part, able to replicate their rankings. Furthermore, while the rankings are similar, we do find that the AHP ranking helps the decision-makers reformulate their choices by taking into account suggestions made by AHP.Decision analysis, Multiple Criteria Decision Aid, Analytic Hierarchy Process (AHP)

Influence of aggregation and measurement scale on ranking a compromise alternative in AHP

Author's pre-print version dated 20. December 2009 deposited in Munich Personal RePEc Archive. Final version published by Palgrave Macmillan; available online at http:// www.palgrave-journals.com/Analytic Hierarchy Process (AHP) is one of the most popular multi-attribute decision aid methods. However, within AHP, there are several competing preference measurement scales and aggregation techniques. In this paper, we compare these possibilities using a decision problem with an inherent trade-off between two criteria. A decision-maker has to choose among three alternatives: two extremes and one compromise. Six different measurement scales described previously in the literature and the new proposed logarithmic scale are considered for applying the additive and the multiplicative aggregation techniques. The results are compared with the standard consumer choice theory. We find that with the geometric and power scales a compromise is never selected when aggregation is additive and rarely when aggregation is multiplicative, while the logarithmic scale used with the multiplicative aggregation most often selects the compromise that is desirable by consumer choice theory

Does AHP help us make a choice? - An experimental evaluation

Author's pre-print version dated 2. August 2010 deposited in Munich Personal RePEc Archive. Final version published by Palgrave Macmillan; available online at http:// www.palgrave-journals.com/In this paper, we use experimental economics methods to test how well Analytic Hierarchy Process (AHP) fares as a choice support system in a real decision problem. AHP provides a ranking that we statistically compare with three additional rankings given by the subjects in the experiment: one at the beginning, one after providing AHP with the necessary pair-wise comparisons and one after learning the ranking provided by AHP. While the rankings vary widely across subjects, we observe that for each individual all four rankings are similar. Hence, subjects are consistent and AHP is, for the most part,able to replicate their rankings. Furthermore, while the rankings are similar, we do find that the AHP ranking helps the decision makers reformulate their choices by taking into account suggestions made by AHP

Influence of aggregation and measurement scale on ranking a compromise alternative in AHP

Analytic Hierarchy Process (AHP) is one of the most popular multi-attribute decision aid methods. However, within AHP, there are several competing preference measurement scales and aggregation techniques. In this paper, we compare these possibilities using a decision problem with an inherent trade-off between two criteria. A decision-maker has to choose among three alternatives: two extremes and one compromise. Six different measurement scales described previously in the literature and the new proposed logarithmic scale are considered for applying the additive and the multiplicative aggregation techniques. The results are compared with the standard consumer choice theory. We find that with the geometric and power scales a compromise is never selected when aggregation is additive and rarely when aggregation is multiplicative, while the logarithmic scale used with the multiplicative aggregation most often selects the compromise that is desirable by consumer choice theory

Does AHP help us make a choice? - An experimental evaluation

In this paper, we use experimental economics methods to test how well Analytic Hierarchy Process (AHP) fares as a choice support system in a real decision problem. AHP provides a ranking that we statistically compare with three additional rankings given by the subjects in the experiment: one at the beginning, one after providing AHP with the necessary pair-wise comparisons and one after learning the ranking provided by AHP. While the rankings vary widely across subjects, we observe that for each individual all four rankings are similar. Hence, subjects are consistent and AHP is, for the most part, able to replicate their rankings. Furthermore, while the rankings are similar, we do find that the AHP ranking helps the decision-makers reformulate their choices by taking into account suggestions made by AHP

A priority assessment multi-criteria decision model for human spaceflight mission planning at NASA

Analog missions are real-life, Earth-based science missions whose purpose is to help understand the operations, techniques, and technologies required to perform similar tasks during future human spaceflight missions. The goal of performing an analog mission is to prepare crewmembers and support teams for future space missions in a low risk, low-cost environment. Vehicle, habitat, and surface terrain simulators are used to test hardware, operations, and tasks repeatedly for analog missions. This study presents a multi-criteria decision making model that was developed for the Integrated Human Exploration Mission Simulation Facility project at Johnson Space Center to assess the priority of a set of human spaceflight mission simulators. The proposed framework integrates subjective judgments derived from the analytic hierarchy process with entropy data into a preference model to prioritize five mission simulators for the human exploration of Mars