Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Extending an outranking multiple criteria decision making method to differentiate gain and loss
Download
Hazel_SENTURK_MS_Thesis.pdf
Date
2021-9-10
Author
Şentürk, Hazel
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
464
views
190
downloads
Cite This
In this study, the integration of Prospect Theory into ranking and sorting methods based on the dominance relations is studied. The well-known multi-criteria ranking method PROMETHEE and the well-known multi-criteria sorting method FlowSort are extended by using the prospect theory perspective. The proposed methods are used to rank and sort the alternatives in the case where the impact of losses is greater than gains for the same amount. When the results are compared with the PROMETHEE and FlowSort methods, the results show how the rankings and classes of the alternatives change according to the value of loss and gain that are determined by the decision-maker.
Subject Keywords
Multi-criteria decision making
,
Prospect theory
,
PROMETHEE
,
FlowSort
,
Outranking relations
URI
https://hdl.handle.net/11511/93194
Collections
Graduate School of Natural and Applied Sciences, Thesis
Suggestions
OpenMETU
Core
A Multiple Criteria Ranking Method Based on Outranking Relations: An Extension for Prospect Theory
Karasakal, Esra; Karasakal, Orhan; Şentürk, Hazel (Springer, London/Berlin , 2022-06-01)
In this study, Prospect Theory is integrated into a well-known multiple criteria ranking method, PROMETHEE. PROMETHEE considers the outranking relations among alternatives based on the preference functions. Prospect Theory evaluates the alternatives with a difference function based on gains and losses. The preference functions of PROMETHEE are modified to capture the choice behavior of the decision maker. The proposed method is a generalization of PROMETHEE that can handle the higher loss impact case as wel...
A Favorable Weight-Based Evolutionary Algorithm for Multiple Criteria Problems
SOYLU, Banu; Köksalan, Mustafa Murat (Institute of Electrical and Electronics Engineers (IEEE), 2010-04-01)
In this paper, we present a favorable weight-based evolutionary algorithm for multiple criteria problems. The algorithm tries to both approximate the Pareto frontier and evenly distribute the solutions over the frontier. These two goals are common for many multiobjective evolutionary algorithms. To achieve these goals in our algorithm, each member selects its own weights for a weighted Tchebycheff distance function to define its fitness score. The fitness scores favor solutions that are closer to the Pareto...
Evolving a hierarchical decision making mechanism using fuzzy logic
Beldek, Ulas; Leblebicioğlu, Mehmet Kemal (2008-12-01)
In this study, a new hierarchical decision-making and decision-fusion mechanism is introduced for solving decision making problems in a consistent manner. This mechanism is constructed by using a genetic algorithm. The proposed mechanism employs fuzzy logic and a performance index determined based on the performance of decision-making agents at successive hierarchical levels. The mechanism is such that the decisions in previous levels are influential on the current level decisions according to the performan...
An interactive ranking-based multi-criteria choice algorithm with filtering: Applications to university selection
Karakaya, Gülşah (Orta Doğu Teknik Üniversitesi (Ankara, Turkey), 2019-6)
In this study, we develop an interactive algorithm to converge to the most preferred alternative of a decision maker (DM) among a set of discrete alternatives. The algorithm presents a limited number of alternatives to the DM and collects preference ranking of them iteratively. The preferences are modeled by a flexible and realistic preference function. To improve the performance, the alternatives presented are determined by a filtering method. We compare our algorithm with benchmark algorithms on nume...
A Probabilistic approach to sparse multi scale phase based stereo
ULUSOY PARNAS, İLKAY; Halıcı, Uğur; HANCOCK, EDWIN (2004-04-30)
In this study, a multi-scale phase based sparse disparity algorithm and a probabilistic model for matching are proposed. The disparity algorithm and the probabilistic approach are verified on various stereo image pairs.
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
H. Şentürk, “Extending an outranking multiple criteria decision making method to differentiate gain and loss,” M.S. - Master of Science, Middle East Technical University, 2021.