Graduation Semester and Year
2017
Language
English
Document Type
Thesis
Degree Name
Master of Science in Computer Science
Department
Computer Science and Engineering
First Advisor
Chengkai Li
Abstract
Analytic Hierarchy Process (AHP) is a Multiple-Criteria Decision-Making MCDM) technique devised by Thomas L. Saaty. In AHP, all the pairwise comparisons between criteria and alternatives in terms of each criterion are used to calculate global rankings of the alternatives. In the classic AHP, the comparisons are provided collectively by a small group of decision makers. We have formulated a technique to incorporate crowd-sourced inputs into AHP. Instead of taking just one comparison for each pair of criteria or alternatives, multiple users are asked to provide inputs. As in AHP, our approach also supports consistency check of the comparison matrices. The key di erence is, in our approach, we do not dismiss the inconsistent matrices or ask users to reevaluate the comparisons. We try to resolve the inconsistency by carefully examining which comparisons are causing the inconsistency the most and then getting more inputs by asking appropriately selected questions to the users. Our approach consists of collecting the data, creating initial pairwise comparison matrices, checking for inconsistencies in the matrices, try to resolve the matrices if inconsistency found and calculating nal rankings of the alternatives.
Keywords
AHP, Crowdsourcing, Analytic Hierarchy Process, Pairwise Comparison
Disciplines
Computer Sciences | Physical Sciences and Mathematics
License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.
Recommended Citation
Timilsina, Ishwor, "Crowdsourcing for Decision Making with Analytic Hierarchy Process" (2017). Computer Science and Engineering Theses. 453.
https://mavmatrix.uta.edu/cse_theses/453
Comments
Degree granted by The University of Texas at Arlington