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.

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 Ranking Methods for Multicriteria Decision-Making: Application to Benchmarking of Solvers and Problems

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Joseph Gogodze
Keyword(s):  
Decision Making ◽  
Multicriteria Decision Making ◽  
Performance Assessments ◽  
Benchmark Problem ◽  
Ranking Methods ◽  
Multicriteria Decision ◽  
Decision Making Problem ◽  
Evolution Algorithms ◽  
Differential Evolution Algorithms

Evaluating the performance assessments of solvers (e.g., for computation programs), known as the solver benchmarking problem, has become a topic of intense study, and various approaches have been discussed in the literature. Such a variety of approaches exist because a benchmark problem is essentially a multicriteria problem. In particular, the appropriate multicriteria decision-making problem can correspond naturally to each benchmark problem and vice versa. In this study, to solve the solver benchmarking problem, we apply the ranking-theory method recently proposed for solving multicriteria decision-making problems. The benchmarking problem of differential evolution algorithms was considered for a case study to illustrate the ability of the proposed method. This problem was solved using ranking methods from different areas of origin. The comparisons revealed that the proposed method is competitive and can be successfully used to solve benchmarking problems and obtain relevant engineering decisions. This study can help practitioners and researchers use multicriteria decision-making approaches for benchmarking problems in different areas, particularly software benchmarking.

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.

On Some Advancements within Certain Multicriteria Decision Making Support Methodology

2013 ◽  
Vol 2 (2) ◽  
pp. 143 ◽  
Author(s):  
Pawel Tadeusz Kazibudzki ◽  
Andrzej Z Grzybowski
Keyword(s):  
Decision Making ◽  
Pairwise Comparison ◽  
Multicriteria Decision Making ◽  
Scientific Paper ◽  
Analytic Hierarchy ◽  
Management Activity ◽  
Multicriteria Decision ◽  
Managerial Decisions ◽  
The Right ◽  
Decision Making Support

Deriving true priority vectors from intuitive pairwise comparison matrices (PCMs) and consistency measurement of decision makers judgments about their genuine weights are crucial issues within the multicriteria decision making support methodology called Analytic Hierarchy Process (AHP). The most popular procedure in the ranking process, constitutes the Right Eigenvector Method (REV). The inventor of the AHP convinces that as long as inconsistent PCMs are allowed in the AHP none of the other existing procedures qualify and the REV provides the only right solution in this process. The objective of this scientific paper is to examine if the former opinion can be considered as experimentally confirmed. For this purpose it was decided to apply Monte Carlo methodology. However, rather than simulate and analyze simulations results for a single PCM, as it has been done so far by many other authors, we decided to design and analyze computer simulations results for a singular model of the AHP framework. Our findings lead to inevitable conclusion that the REV cannot longer be perceived as a dominant procedure within the AHP methodology, especially when nonreciprocal PCMs are considered. It was verified empirically in our research that in the situation when nonreciprocal PCMs are considered the REV impoverishes the entire AHP methodology by its lack of PCMs inconsistency measure in such cases. Moreover, it provides less accurate rankings for a particular decision in comparison to other presented methods. It was also unequivocally verified that the enforced reciprocity of PCM leads directly to worse estimates of priorities weights. Altogether, it seems very important from the perspective of methodology supporting multicriteria decision making, the crucial process embedded in most of management activity. In the consequence, because the REV recedes other prioritization procedures available for the AHP methodology, it is advised to consider them instead, especially under some circumstances of an important and very tight managerial decisions.

scholarly journals FINDING A PROMISING VENTURE CAPITAL PROJECT WITH TODIM UNDER PROBABILISTIC HESITANT FUZZY CIRCUMSTANCE

2018 ◽  
Vol 24 (5) ◽  
pp. 2026-2044 ◽  
Author(s):  
Weike Zhang ◽  
Jiang Du ◽  
Xiaoli Tian
Keyword(s):  
Decision Making ◽  
Group Decision ◽  
Venture Capitalists ◽  
Fuzzy Information ◽  
Investment Environment ◽  
Limited Ability ◽  
Risk Seeking ◽  
Decision Making Problem ◽  
Criteria Weights

Considering the risk aversion for gains and the risk seeking for losses of venture capitalists, the TODIM has been chosen as the decision-making method. Moreover, group decision is an available way to avoid the limited ability and knowledge etc. of venture capitalists. Simultaneously, venture capitalists may be hesitant among several assessed values with different probabilities to express their real perception because of the uncertain decision-making environment. However, the probabilistic hesitant fuzzy information can solve such problems effectively. Therefore, the TODIM has been extended to probabilistic hesitant fuzzy circumstance for the sake of settling the decision-making problem of venture capitalists in this paper. Moreover, due to the uncertain investment environment, the criteria weights are considered as probabilistic hesitant fuzzy information as well. Then, a case study has been used to verify the feasibility and validity of the proposed TODIM. Also, the TODIM with hesitant fuzzy information has been carried out to analysis the same case. From the comparative analysis, the superiority of the proposed TODIM in this paper has already appeared.

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