Interpretation of criteria weights in multicriteria decision making

1999 ◽  
Vol 37 (3) ◽  
pp. 527-541 ◽  
Author(s):  
Eng U. Choo ◽  
Bertram Schoner ◽  
William C. Wedley
SAGE Open ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 215824402110360
Author(s):  
Fengsheng Chien ◽  
Chia-Nan Wang ◽  
Ka Yin Chau ◽  
Van Thanh Nguyen ◽  
Viet Tinh Nguyen

The uses and management of capital is extremely important to the operation of any businesses. However, not all businesses have available capital, so the use of loans in many different forms is always an effective solution in managing corporate finance. Accompanying with businesses, many financial leasing companies have implemented products and programs to lend money to businesses with low interest rates. So, choosing the best financial leasing company is a primary concern of businesses. To increase competitiveness, financial leasing companies often offer preferential conditions to attract businesses. Choosing the best financial leasing service to leasing is important and necessary to those businesses. Thus, the selection of a financial leasing company by small and medium enterprises benefits from the application of Multicriteria Decision-Making (MCDM) methods which allows the decision maker to consider various qualitative and quantitative criteria. In this article, the author applied Fuzzy Analytical Network Process (FANP) to calculate the related criteria weights of the financial leasing company selection problem of businesses. Then, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is applied to rank the potential decision-making units. This research establishes one complete and efficient model for financial leasing company selection using FANP and TOPSIS methods. The proposed model is then applied into a real-world case study to demonstrate its feasibility.


2011 ◽  
Vol 52-54 ◽  
pp. 1868-1872
Author(s):  
Liang Liang ◽  
Ren Yan Jiang ◽  
Yin Liang

It is difficult to obtain the correct criteria weights with uncertain information in the multicriteria decision-making. Many methods depend on the subjective estimate. Therefore, a method is presented to evaluate the samples ranking only need the importance order of criteria. It evaluates firstly the overall ranking scores of samples based on the graphical classification and multicriteria hierarchical integrated methods. Subsequently, the relation model between the criteria scores and overall ranking scores of samples is built by linear regression. Finally, a fincial credit loan decision-making problem is presented to describe the way of the multicriteria decisiion making process. The analysis to compare with the AHP method illustrates the proposed method is objective and effective.


2010 ◽  
Vol 16 (2) ◽  
pp. 159-172 ◽  
Author(s):  
Edmundas Kazimieras Zavadskas ◽  
Zenonas Turskis

Multicriteria decision‐making (MCDM) methods are used in many areas of human activities. Each alternative in a multicriteria decision‐making problem can be described by a set of criteria. Criteria can be qualitative and quantitative. They usually have different units of measurement and a different optimization direction. The normalization aims at obtaining comparable scales of criteria values. The paper introduces a new Additive Ratio ASsessment (ARAS) method. In order to illustrate the described ARAS method a real case study of evaluation of microclimate in office rooms is presented. The case study aims to determine the inside climate of the premises, where people work, and to define measures to be taken to improve their environment. Based on the analysis, the following criteria for inside climate evaluation are suggested: air turnover inside the premises, air humidity, air temperature, illumination intensity, air flow rate, and dew point. The criteria weights were determined by the method of pairwise comparison based on the estimates of experts. Santrauka Daugiakriteriniai sprendimų metodai taikomi daugelyje žmogaus veiklos sričių. Kiekviena alternatyva, sprendžiant daugiakriterinius uždavinius, gali būti apibūdinta kriteriju aibe. Kriterijai gali būti kokybiniai ir kiekybiniai. Jie paprastai turi skirtingus matavimo vienetus ir įvairią optimizavimo kryptį. Kriterijų vertės yra normalizuojamos lyginamos skalės vertėms gauti. Straipsnyje pateikiamas naujas adityvinis kriterijų santykių įvertinimo metodas (ARAS) daugiakriteriniams uždaviniams spręsti. ARAS metodo taikymui pavaizduoti pateiktas realus mikroklimato biuro patalpose vertinimo tyrimas. Tyrimo tikslas ‐ įvertinti patalpų, kurioje žmonės dirba, mikroklimata ir nustatyti priemones, kurių reikia imtis aplinkai pagerinti. Remiantis uždavinio tikslų analize, siūlomi šie kriterijai vidaus klimatui įvertinti: oro pasikeitimas, patalpų oro santykinė dregmė, oro temperatūra, apšvietimo intensyvumas, oro srautas ir rasos taškas. Kriterijų svoriai nustatomi porinio lyginimo metodu, remiantis ekspertų vertinimais. Kriterijų reikšmės nustatytos sertifikuotu prietaisu.


Author(s):  
Luisa Andrea González-Cruz ◽  
Luis Fernando Morales-Mendoza ◽  
Alberto Alfonso Aguilar-Lasserre ◽  
Catherine Azzaro-Pantel ◽  
Paulina Martínez-Isidro ◽  
...  

Author(s):  
Jian Li ◽  
Li-li Niu ◽  
Qiongxia Chen ◽  
Zhong-xing Wang

AbstractHesitant fuzzy preference relations (HFPRs) have been widely applied in multicriteria decision-making (MCDM) for their ability to efficiently express hesitant information. To address the situation where HFPRs are necessary, this paper develops several decision-making models integrating HFPRs with the best worst method (BWM). First, consistency measures from the perspectives of additive/multiplicative consistent hesitant fuzzy best worst preference relations (HFBWPRs) are introduced. Second, several decision-making models are developed in view of the proposed additive/multiplicatively consistent HFBWPRs. The main characteristic of the constructed models is that they consider all the values included in the HFBWPRs and consider the same and different compromise limit constraints. Third, an absolute programming model is developed to obtain the decision-makers’ objective weights utilizing the information of optimal priority weight vectors and provides the calculation of decision-makers’ comprehensive weights. Finally, a framework of the MCDM procedure based on hesitant fuzzy BWM is introduced, and an illustrative example in conjunction with comparative analysis is provided to demonstrate the feasibility and efficiency of the proposed models.


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