The theory of ratio scale estimation: Saaty's analytic hierarchy process
Management Science
Quantifying judgmental uncertainty: Methodology, experiences, and insights
IEEE Transactions on Systems, Man and Cybernetics
Using the analytic hierarchy process for information system project selection
Information and Management
Remarks on the analytic hierarchy process
Management Science
Reply to “remarks on the analytic hierarchy process” by J. S. Dyer
Management Science
A clarification of “remarks on the analytic hierarchy process”
Management Science
Group decision support with the analytic hierarchy process
Decision Support Systems
A multiple criteria decision model for information system project selection
Computers and Operations Research
Multiple criteria R&D project selection and scheduling using fuzzy logic
Computers and Operations Research
A web-based multi-perspective decision support system for information security planning
Decision Support Systems
A hybrid fuzzy group decision support framework for advanced-technology prioritization at NASA
Expert Systems with Applications: An International Journal
Computers and Industrial Engineering
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Evaluating and prioritizing advanced-technology projects is a particularly difficult task for the staff at the Kennedy Space Center (KSC) shuttle project engineering office. Because the evaluation process is complex and unstructured, decision makers (DMs) must consider vast amounts of diverse information concerning safety, systems engineering, cost savings, process enhancement, reliability, and implementation. Intuitive methods developed in the past have helped them to use large volumes of information in evaluating projects. However, these intuitive methods do not provide a structured framework for systematic evaluation. CROSS (consensus-ranking organizational-support system) is a multicriteria group-decision-making model that I implemented successfully at KSC to capture the DMs' beliefs through sequential, rational, and analytical processes. CROSS uses the analytic hierarchy process (AHP), subjective probabilities, the entropy concept, and the maximize-agreement heuristic (MAH) to enhance the DMs' intuition in evaluating sets of projects.