SECTOR SUBJECT METHOD RESOURCE
Education
SELECTION PhD STUDENT USING VIKOR METHOD IN THE BASED OF AHP
AHP-VIKOR
SOBA, M , Şimşek, A , Erdin, E , Can, A . (2016). AHP TEMELLİ VIKOR YÖNTEMİ İLE DOKTORA ÖĞRENCİ SEÇİMİ. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, (50), 109-132. Retrieved from http://dergipark.gov.tr/dpusbe/iss ue/26797/282643 Finance A DECISION SUPPORT SYSTEM (DSS) PROPOSAL WITH AHPVIKOR INTEGRATION IN THE EVALUATION OF INVESTMENT PROJECTS AHP-VIKOR Gökşen, Y , Çevik, E . (2016). YATIRIM PROJELERİNİN DEĞERLENDİRİLMESİNDE AHP-VIKOR ENTEGRASYONU İLE BİR KDS ÖNERİSİ. Ege Stratejik Araştırmalar Dergisi, 7 (2), 219- 235. DOI: 10.18354/esam.32181 Textil SUPPLIER SELECTION WITH AHP-VIKOR INTEGRATED METHOD: TEXTILE INDUSTRY APPLICATION AHP-VIKOR KARA, İ , ECER, F . (2016). AHP-VIKOR ENTEGRE YÖNTEMİ İLE TEDARİKÇİ SEÇİMİ: TEKSTİL SEKTÖRÜ UYGULAMASI. Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 18 (2), 255- 272. DOI:
10.16953/deusbed.78956
Supply Chain
SELECTION OF THE BEST SUPPLIER WITH THE AHP-VIKOR METHOD AND AN APPLICATION
AHP-VIKOR
ARSLAN, H . (2017). AHP- VIKOR YÖNTEMİ İLE ETKİN TASARRUFA YÖNELİK EN İYİ TEDARİKÇİ SEÇİMİ. Elektronik Sosyal Bilimler Dergisi, 16 (63), 1203-1217. DOI: 10.17755/esosder.305241 Software SELECTING SOFTWARE PROGRAMS FOR ENTERPRISE PROJECT MANAGEMENT WITH AHP AND TOPSIS
AHP-VIKOR
ÖMÜRBEK, N , MAKAS, Y , ÖMÜRBEK, V . (2015). AHP VE TOPSIS YÖNTEMLERİ İLE KURUMSAL PROJE YÖNETİM YAZILIMI SEÇİMİ. Süleyman Demirel Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, (21), 59-83. Retrieved from
http://dergipark.gov.tr/sbe/issue/ 23146/247242
Accommodation
STAFF SELECTION IN ACCOMODATION BUSINESS ON THE BASIS OF AHP AND VIKOR METHOD
AHP-VIKOR
Tarcan İçigen, E , İpekçi Çetin, E . (). AHP TEMELLİ TOPSİS YÖNTEMİ İLE KONAKLAMA İŞLETMELERİNDE
PERSONEL SEÇİMİ. Balkan Sosyal Bilimler Dergisi, 7 (13), 179-187. Retrieved from http://dergipark.gov.tr/bsbd/issue /34559/337848 Supplier Selection SUPPLIER SELECTION IN AN AUTOMOTIVE INDUSTRY FIRM: AHP- FUZZY AHP AND TOPSIS APPLICATION AHP-VIKOR ALKAN, A , ALADAĞ, Z , ÇELİK, C . (2016). OTOMOTİV SEKTÖRÜNDE FAALİYET GÖSTEREN BİR FİRMADA TEDARİKÇİ SEÇİMİ: AHP-BULANIK AHP ve TOPSIS UYGULAMASI. Beykent Üniversitesi Fen ve Mühendislik Bilimleri Dergisi, 9 (1), 0-0. DOI:
10.20854/bujse.258169
As can be understood from the literature table above, AHP and Vikor methods have been used in many sectors, including the automotive sector, but these have been limited to supplier selection, software selection and staff selection. There is no method in automotive sectors to select in WAREHOUSE location determination technology.
9. ANALYTIC HIERARCHY PROCESS (AHP)
The analytic hierarchy process is a decision making technique by Thomas L. Saaty to facilitate the decision-making of businesses in the 1970s. Decision-making is to select the most appropriate option in view of the sources and constraints on the track to reach any goal. (Atlas & Keçek, 2000) decision-making is a mental process that we encounter in all areas of life and at once. The AHP is actually a methodology that people use instinctively in decision-making, but they do not.
AHP is an approach that analyzes the decisions by comparing the quantifiable concrete or abstract criteria and determines the importance rankings by calculating the priorities according to each other.. (Güngör & Büyüker, 2005) AHP is a fundamental part of a complex and non-structural situation; incorporating these parts or variables into a hierarchical order, translating subjective evaluations made for each variable into numerical values, examining subjective
evaluations to determine which of the variables will affect the results of the particular situation and has the highest priority.
AHP has developed the work of analyzing complex situations and making complex decisions, since Saaty's awareness of the need for accurate mathematics, not complex mathematics, to succeed in the decision-making process; hierarchically structured and visualized complex, multi-personality, multi-criteria and multi-period problems. For this reason, AHP is used effectively by the managers in solving various problems in country problems and in many sectors.
10. THEORETICAL FUNCTION OF AHP
AHP is a technique that allows multi-criteria variables belonging to a probing to be sorted and prioritized in a hierarchical structure. When assessed in this context, AHP's problem solving process is based on 3 basic principles. These; Decomposition is the principle of comparative judgments and synthesis of priorities. (Başkaya & Akar, 2005) The AHP process proposed by Saaty consists of 4 simple axioms.
Axiom 1 (inversion) is the fulfillment of the adverse condition while determining or comparing the strengths of the preferences when deciding or comparing. A cluster. binary comparisons of any two i and j alternatives with significance ratings wi and wj in this set of alternatives, under any criterion c in the set of C criteria;
Since at least one of the comparison matrices is known, the corresponding axiom is found in this number, so the inverted axiom plays an auxiliary role in forming the comparison matrix.
Axiom 2 (Homogeneity): In binary comparisons, one of two criteria can not be considered to be superior to the other infinitely. That is, ∞ ≠ ija (for ∀i and j'ler) dir. Since the basic scale used (Table 1) is
between 1-9, aij values will take a value between 1/9, 1/8, ..., 1, ..., 7,8,9.(Akay, Çetinyokuş, & Dağderviren, 2014)
Axiom 3 (Independence): Judgments on hierarchical elements do not depend on lower-level members. This axiom is based onthe creation of the hierarchical structure. (Forman & Saul, 2001)
Axiom 4 (Expectations): Each criterion affecting the current decision problem must be shown in the alternative hierarchy. In other words, all intuitions of decision makers should be reflected as criteria or alternatives. (Saaty, Mathematical Methods of Operations Research, 1988)
11. AHP PROCESS STEPS
AHP Method; level hierarchical structure of goals, criteria, sub- criteria and alternatives. In this structure, the importance of each decision criterion is obtained through binary comparisons and the performance of each alternative is evaluated against each criterion. (Triantaphyllou & Mann, 1995) The application steps of this method, first worked by Saaty in 1986, are given below. (Kamal & Harbi, 2001)
1. The problem should be clearly defined and the objectives in the problem determined.
2. To begin with the aim, the main criteria and the alternatives at the bottom level are introduced into a hierarchical structure
3. To determine which of the alternatives and criteria is more dominant, binary comparisons between alternatives and criteria are made using the scale described in Table 2, and these comparison matrices (nxn) are square matrix size. When Comparison and matrices are generated, the binary comparison in Table 2 is used. (Saaty, Axiomatic foundation of the Analytic Hierarchy Process. , 1986) 4. In order to normalize each column in the binary comparison matrix, column sums are taken and the normalized matrix is formed by
dividing the elements of the matrix by the sum of the respective columns.
5. The priority vector matrix is obtained by taking the row totals of the normalized matrix created for each alternative or criterion.
6. The priority values generated for each criterion or alternative in the priority matrix obtained by the priority vector are multiplied by the column elements of the binary comparison matrix of that criterion or alternate and the weighted total matrix is obtained.
7. The sum of the row values of the weighted total matrix is divided by the row values of the priority vector matrix, and the priority values of the criteria or alternatives are obtained by taking the arithmetic mean of the elements of the formed matrix (nx1).
8. While calculating the consistency index (Saaty, 1990); firstly the CI value is found.
CI = (λ Max-n) / (n-1) CI: Consistency Index
9. The consistency ratio can be calculated with the coincidence of the randomness table values and CI expressed in Table 1. (Saaty, The Analytic Hierarchy Process, 1980)
CR: Consistency Indicator RI: Stochastic Indicator The consistency ratio in the AHP method should be less than 0.10. If the value found is greater than 0.1, the binary comparison matrix should be checked again and the steps to be made are repeated step by step.
10. The priorities of the alternatives calculated in the framework of the criterion are multiplied for each alternative of the priorities resulting from the binary comparison between the criteria and the desired final priority value can be calculated.