Mühendislik Fakültesi / Faculty of Engineering

Permanent URI for this collectionhttps://hdl.handle.net/11727/1401

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Author: search.filters.author.Toktas, PelinSubject: search.filters.subject.MCDM

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    A Novel Multi-Criteria Decision-Making Approach Proposal Based on Kemira-M with Four Criteria Groups
    (2022) Ay, Sefacan; Can, Gulin Feryal; Toktas, Pelin
    This study aims to eliminate the subjectivity in the weight assignment process of Modified Kemeny Median Indicator Ranks Accordance (KEMIRA-M) and to remove the need for experts to reach a consensus on determining the criteria weights. Additionally, this study aims to apply KEMIRA-M for four different criteria groups and to prevent some criteria from taking a weight value of "0", as in other studies using KEMIRA-M. In this context, the weighting procedure of KEMIRA-M is advanced using three different ranking-based weighting methods such as Rank Sum (RS), Rank Exponent (RE) and Rank Reciprocal (RR) to operate Median Priority Components (MPCs) more effectively. Accordingly, to determine which weighting method for which criterion group is more suitable, the selection procedure of KEMIRA-M was applied and alternative rankings were obtained for 81 different weight set combinations. Additionally, MATLAB codes have been used to provide flexibility for the application of the proposed approach in a supplier selection problem selected for a case study.
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    Warehouse Location selection for an electricity distribution company by KEMIRA-M method
    (2020) Kis, Oznil; Can, Gulin Feryal; Toktas, Pelin
    In this study, by using Modified Kemeny Median Indicator Ranks Accordance (KEMIRA-M) approach which begins to become popular in recent times for solution of Multi criteria Decision Making (MCDM) problems, warehouse location selection for an electricity distribution company is performed. KEMIRA-M logically distinguishes criteria into two groups and it computes criteria importance weights by including interactions between both groups. KEMIRA-M considers both decision makers' preferences related to the priorities of criteria and quantitative or qualitative values of these criteria in decision making process. Decision makers can change importance weights of criteria based on median priority component representing expected rankings of criteria importance weights and they can see the effect of this variability on rankings of alternatives. In warehouse location selection problem investigated in this study, it is aimed to choose the favorable location considering different criteria and these criteria were grouped firm related and environmental criteria to evaluate 20 alternative warehouse locations. In this context, as firm related criteria; Operation Center-Meeting Point (OC-MP) transportation cost per month, main warehouses' transportation costs per month, number of connected OC-MP, consumption amounts of OC-MP were considered. Population, distance to the closest main road, average distance to main supplier, mobility, investment amounts in 2018, average delivery time and land cost were taken into account as environmental criteria group.
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    Stochastic KEMIRA-M Approach with Consistent Weightings
    (2019) Toktas, Pelin; Can, Gulin Feryal
    This study proposes an advanced Modified KEmeny Median Indicator Rank Accordance (KEMIRA-M) approach based on stochastic evaluation process considering consistent weights to improve effective usage of KEMIRA-M. In the proposed approach, tasks related to the decision issue are performed by decision makers to ensure the understanding sufficiency of alternatives in terms of criteria more clearly. The weighting procedure of Analytic Hierarchy Process (AHP) is implemented in a stochastic manner benefited from discrete uniform distribution to provide obtaining consistent criteria weights considering median priority components. Therefore, different trials including different number of replications that shows the number of decision makers are performed and the most consistent weightings are determined for each trial in the stochastic process. In this way, the dependency to the limited numbers of decision makers and to determine criteria weights in a heuristic manner in KEMIRA-M is prevented. Additionally, the effect of the number of decision makers on criteria weightings and alternatives' ranking process is shown. To obtain the most consistent weighting results, this stochastic process is utilized until acquiring approximate consistency ratios. The proposed stochastic KEMIRA-M approach is utilized to rank nine shopping malls (SMs) in Ankara in terms of technical criteria (TC) and universal design criteria (UDC). It was seen from the ranking results that the first SM (SM1) is the best one.