A Probabilistic and interactive approach to multiple criteria sorting

Mutlu, Sinem
In this thesis, we develop a method in order to assign alternatives that are evaluated by multiple criteria into preference ordered classes probabilistically. Our motivation is that; when there are large sets of alternatives, placement could be realized in a fast and effective way based on a reasonable misclassification ratio. We assume that the underlying utility function of Decision Maker (DM) is additive. We first ask DM to place reference alternatives into the classes. We develop an interactive probabilistic sorting approach that calculates the probability of each alternative being in each class. If all the alternatives can be placed into a class at the same time by evaluating probabilities, the procedure ends, if not DM is asked to place an unassigned alternative into a class and the procedure is repeated by utilizing this new information. The procedure ends when all the alternatives are placed. We test the performance of the algorithms on four different problems. The performance of algorithm is evaluated by number of misclassified alternatives, expected number of misclassified alternatives, and number of alternatives that are asked to the DM for placement.


An interactive approach for placing alternatives in preference classes
Köksalan, Mustafa Murat; Ulu, C (2003-01-16)
In this paper, we consider the multiple criteria decision making problem of partitioning alternatives into preference classes. We develop an interactive procedure based on the assumption that the decision maker (DM) has a linear utility function. The approach requires the DM to place an alternative in a preference class from time to time. Based on the preference information derived from the DM's placement as well as from dominance and linearity, we try to place other alternatives. We present results on the ...
A Mathematical programming evaluation approach for multiple criteria sorting problems
Civelek, Merve; Karasakal, Esra; Department of Operational Research (2019)
Multiple criteria sorting problem is to assign alternatives, evaluated according to multiple criteria, into predefined preference ordered classes. In this study, a new distance metric based sorting method is developed to solve multiple criteria sorting problems without specifying class thresholds between preference-ordered classes. The aim of the proposed method is to assign each alternative to one class or a set of possible adjacent classes considering the distance to class centroids. In the proposed metho...
A probabilistic approach to multi criteria sorting problem
Buğdacı, Aslı Gül; Köksalan, Murat; Department of Industrial Engineering (2009)
We aim to classify alternatives evaluated in multiple criteria among preference ordered classes assuming an underlying additive utility function. We develop a probabilistic classification method by calculating the probability of an alternative being in each class. We assign alternatives to classes based on threshold probabilities. We require the decision maker to place an alternative to a class when no alternatives satisfy the required thresholds. We find new probabilities for unassigned alternatives in the...
An interactive probabilistic approach to multi-criteria sorting
BUGDACI, Asli Gul; KOKSALAN, Murat; Ozpeynirci, Selin; Serin, Yaşar Yasemin (2013-10-01)
This article addresses the problem of sorting alternatives evaluated by multiple criteria among preference-ordered classes. An interactive probabilistic sorting approach is developed in which the probability of an alternative being in each class is calculated and alternatives are assigned to classes keeping the probability of incorrect assignments below a specified small threshold value. The decision maker is occasionally required to place alternatives to classes. The probabilities for unassigned alternativ...
Issues in selecting a representative set for multi-objective integer programs
Özarık, Sami Serkan; Lokman, Banu; Köksalan, Murat; Department of Industrial Engineering (2017)
Multi-objective Integer Programs (MOIPs) have many areas of application in real life since it allows the decision makers to consider conflicting objectives simultaneously. However, the optimal solution is not unique for MOIPs and the number of nondominated points of multi-objective integer programs increases exponentially with the problem size. Therefore, finding all nondominated points is computationally hard and not practical for the decision maker. Instead of generating all nondominated points, it is rea...
Citation Formats
S. Mutlu, “A Probabilistic and interactive approach to multiple criteria sorting,” M.S. - Master of Science, Middle East Technical University, 2015.