A Multicriteria Decision Method with Uncertain Information in Financial Credit Loan Decision-Making

2011 ◽  
Vol 52-54 ◽  
pp. 1868-1872
Author(s):  
Liang Liang ◽  
Ren Yan Jiang ◽  
Yin Liang
Keyword(s):  
Decision Making ◽  
Multicriteria Decision Making ◽  
Uncertain Information ◽  
Ahp Method ◽  
Multicriteria Decision ◽  
Decision Making Problem ◽  
Financial Credit ◽  
Criteria Weights ◽  
Relation Model ◽  
Integrated Methods

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.

scholarly journals A NEW ADDITIVE RATIO ASSESSMENT (ARAS) METHOD IN MULTICRITERIA DECISION‐MAKING / NAUJAS ADITYVINIS KRITERIJŲ SANTYKIŲ ĮVERTINIMO METODAS (ARAS) DAUGIAKRITERINIAMS UŽDAVINIAMS SPRĘSTI

2010 ◽  
Vol 16 (2) ◽  
pp. 159-172 ◽  
Author(s):  
Edmundas Kazimieras Zavadskas ◽  
Zenonas Turskis
Keyword(s):  
Decision Making ◽  
Pairwise Comparison ◽  
Multicriteria Decision Making ◽  
Dew Point ◽  
Air Flow Rate ◽  
Multicriteria Decision ◽  
Decision Making Problem ◽  
Criteria Weights ◽  
Office Rooms

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.

scholarly journals A Modified TOPSIS Method Based onDNumbers and Its Applications in Human Resources Selection

2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Liguo Fei ◽  
Yong Hu ◽  
Fuyuan Xiao ◽  
Luyuan Chen ◽  
Yong Deng
Keyword(s):  
Decision Making ◽  
Human Resources ◽  
Multicriteria Decision Making ◽  
Uncertain Information ◽  
Human Beings ◽  
Topsis Method ◽  
Decision Matrix ◽  
Multicriteria Decision ◽  
Decision Making Problem ◽  
Modified Topsis

Multicriteria decision-making (MCDM) is an important branch of operations research which composes multiple-criteria to make decision. TOPSIS is an effective method in handling MCDM problem, while there still exist some shortcomings about it. Upon facing the MCDM problem, various types of uncertainty are inevitable such as incompleteness, fuzziness, and imprecision result from the powerlessness of human beings subjective judgment. However, the TOPSIS method cannot adequately deal with these types of uncertainties. In this paper, aD-TOPSIS method is proposed for MCDM problem based on a new effective and feasible representation of uncertain information, calledDnumbers. TheD-TOPSIS method is an extension of the classical TOPSIS method. Within the proposed method,Dnumbers theory denotes the decision matrix given by experts considering the interrelation of multicriteria. An application about human resources selection, which essentially is a multicriteria decision-making problem, is conducted to demonstrate the effectiveness of the proposedD-TOPSIS method.

scholarly journals Sustainability in the Business Sector: A Fuzzy Multicriteria Decision-Making Model for Financial Leasing Company Selection of the Vietnamese SMEs

SAGE Open ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 215824402110360
Author(s):  
Fengsheng Chien ◽  
Chia-Nan Wang ◽  
Ka Yin Chau ◽  
Van Thanh Nguyen ◽  
Viet Tinh Nguyen
Keyword(s):  
Decision Making ◽  
Interest Rates ◽  
Small And Medium Enterprises ◽  
Multicriteria Decision Making ◽  
Primary Concern ◽  
Multicriteria Decision ◽  
Financial Leasing ◽  
Criteria Weights ◽  
Leasing Company ◽  
Selection Of

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.

scholarly journals Pythagorean Fuzzy (R,S)-Norm Information Measure for Multicriteria Decision-Making Problem

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Abhishek Guleria ◽  
Rakesh Kumar Bajaj
Keyword(s):  
Decision Making ◽  
Fuzzy Set ◽  
Multicriteria Decision Making ◽  
Information Measure ◽  
Present Communication ◽  
Pythagorean Fuzzy Set ◽  
Numerical Examples ◽  
Multicriteria Decision ◽  
Decision Making Problem ◽  
Future Work

In the present communication, a parametric (R, S)-norm information measure for the Pythagorean fuzzy set has been proposed with the proof of its validity. The monotonic behavior and maximality feature of the proposed information measure have been studied and presented. Further, an algorithm for solving the multicriteria decision-making problem with the help of the proposed information measure has been provided keeping in view of the different cases for weight criteria, when weights are unknown and other when weights are partially known. Numerical examples for each of the case have been successfully illustrated. Finally, the work has been concluded by providing the scope for future work.

scholarly journals Systemic Approach to Decision Making

2017 ◽  
pp. 1-16
Keyword(s):  
Decision Making ◽  
Multicriteria Decision Making ◽  
Qualitative Evaluation ◽  
Systemic Approach ◽  
Multicriteria Decision ◽  
Decision Making Problem ◽  
Method Of Solution ◽  
Basic Concepts

Chapter 1 describes the basic concepts and definitions of the theory of decision-making. A general formulation of the problem of decision-making is given. Contents of the problem and multicriteria decision-making problem have been considered. Statement of the problem is formulated. The method of solution is proposed. Qualitative evaluation of alternatives method is reviewed. Illustrative example is given.

NOVEL ENTROPY MEASURE OF A FUZZY SET AND ITS APPLICATION TO MULTICRITERIA DECISION MAKING WITH FUZZY TOPSIS

2021 ◽  
Vol 16 (7) ◽  
Author(s):  
Manzoor Hussain
Keyword(s):  
Decision Making ◽  
Fuzzy Set ◽  
Daily Life ◽  
Multicriteria Decision Making ◽  
Fuzzy Topsis ◽  
Vital Role ◽  
Entropy Measure ◽  
Numerical Comparison ◽  
Uncertain Information ◽  
Multicriteria Decision

Fuzzy entropy is being used to measure the uncertainty with high precision and accuracy than classical crisp set theory. It plays a vital role in handling complex daily life problems involving uncertainty. In this manuscript, we first review several existing entropy measures and then propose novel entropy to measure the uncertainty of a fuzzy set. We also construct an axiomatic definition based on the proposed entropy measure. Numerical comparison analysis is carried out with existing entropies to show the reliability and practical applicability of our proposed entropy measure. Numerical results show that our suggested entropy is reasonable and appropriate in dealing with vague and uncertain information. Finally, we utilize our proposed entropy measure to construct fuzzy TOPSIS (Technique for Ordering Preference by Similarity to Ideal Solution) method to manage Multicriteria decision-making problems related to daily life settings. The final results demonstrate the practical effectiveness and applicability of our proposed entropy measure

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