A new algorithm for a nonlinear multicriteria decision-making problem

1985 ◽  
Vol 132 (3) ◽  
pp. 118
Author(s):  
P.V. Rao ◽  
T.C. Kong ◽  
V.V. Sastry
Keyword(s):  
Decision Making ◽  
Multicriteria Decision Making ◽  
Multicriteria Decision ◽  
Decision Making Problem

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 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.

scholarly journals Algorithms for Multipolar Interval-Valued Neutrosophic Soft Set with Information Measures to Solve Multicriteria Decision-Making Problem

2021 ◽  
Vol 2021 ◽  
pp. 1-29
Author(s):  
Rana Muhammad Zulqarnain ◽  
Imran Siddique ◽  
Aiyared Iampan ◽  
Ebenezer Bonyah
Keyword(s):  
Decision Making ◽  
Similarity Measures ◽  
Weighted Average ◽  
Correlation Coefficients ◽  
Multicriteria Decision Making ◽  
Soft Set ◽  
Multicriteria Decision ◽  
Information Measures ◽  
Decision Making Problem ◽  
Interval Valued

Similarity measures (SM) and correlation coefficients (CC) are used to solve many problems. These problems include vague and imprecise information, excluding the inability to deal with general vagueness and numerous information problems. The main purpose of this research is to propose an m-polar interval-valued neutrosophic soft set (mPIVNSS) by merging the m-polar fuzzy set and interval-valued neutrosophic soft set and then study various operations based on the proposed notion, such as AND operator, OR operator, truth-favorite, and false-favorite operators with their properties. This research also puts forward the concept of the necessity and possibility operations of mPIVNSS and also the m-polar interval-valued neutrosophic soft weighted average operator (mPIVNSWA) with its desirable properties. Cosine and set-theoretic similarity measures have been proposed for mPIVNSS using Bhattacharya distance and discussed their fundamental properties. Furthermore, we extend the concept of CC and weighted correlation coefficient (WCC) for mPIVNSS and presented their necessary characteristics. Moreover, utilizing the mPIVNSWA operator, CC, and SM developed three novel algorithms for mPIVNSS to solve the multicriteria decision-making problem. Finally, the advantages, effectiveness, flexibility, and comparative analysis of the developed algorithms are given with the prevailing techniques.

Multicriteria Decision Making Using Double Refined Indeterminacy Neutrosophic Cross Entropy and Indeterminacy Based Cross Entropy

2016 ◽  
Vol 859 ◽  
pp. 129-143 ◽  
Author(s):  
Ilanthenral Kandasamy ◽  
Florentin Smarandache
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Multicriteria Decision Making ◽  
Cross Entropy ◽  
Neutrosophic Set ◽  
Neutrosophic Sets ◽  
Multicriteria Decision ◽  
Inconsistent Information ◽  
Decision Making Problem ◽  
The Cross

Double Refined Indeterminacy Neutrosophic Set (DRINS) is an inclusive case of the refined neutrosophic set, defined by Smarandache (2013), which provides the additional possibility to represent with sensitivity and accuracy the uncertain, imprecise, incomplete, and inconsistent information which are available in real world. More precision is provided in handling indeterminacy; by classifying indeterminacy (I) into two, based on membership; as indeterminacy leaning towards truth membership (IT) and indeterminacy leaning towards false membership (IF). This kind of classification of indeterminacy is not feasible with the existing Single Valued Neutrosophic Set (SVNS), but it is a particular case of the refined neutrosophic set (where each T, I, F can be refined into T1, T2, ...; I1, I2, ...; F1, F2, ...). DRINS is better equipped at dealing indeterminate and inconsistent information, with more accuracy than SVNS, which fuzzy sets and Intuitionistic Fuzzy Sets (IFS) are incapable of. Based on the cross entropy of neutrosophic sets, the cross entropy of DRINSs, known as Double Refined Indeterminacy neutrosophic cross entropy, is proposed in this paper. This proposed cross entropy is used for a multicriteria decision-making problem, where the criteria values for alternatives are considered under a DRINS environment. Similarly, an indeterminacy based cross entropy using DRINS is also proposed. The double valued neutrosophic weighted cross entropy and indeterminacy based cross entropy between the ideal alternative and an alternative is obtained and utilized to rank the alternatives corresponding to the cross entropy values. The most desirable one(s) in decision making process is selected. An illustrative example is provided to demonstrate the application of the proposed method. A brief comparison of the proposed method with the existing methods is carried out.

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 Novel Method for Dynamic Multicriteria Decision Making with Hybrid Evaluation Information

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Shihu Liu ◽  
Tauqir Ahmed Moughal
Keyword(s):  
Decision Making ◽  
Fuzzy Number ◽  
Multicriteria Decision Making ◽  
Intuitionistic Fuzzy Number ◽  
Multicriteria Decision ◽  
Intuitionistic Fuzzy ◽  
Decision Making Problem ◽  
Ideal Solutions ◽  
Interval Valued ◽  
Evaluation Information

How to select the most desirable pattern(s) is often a crucial step for decision making problem. By taking uncertainty as well as dynamic of database into consideration, in this paper, we construct a dynamic multicriteria decision making procedure, where the evaluation information of criteria is expressed by real number, intuitionistic fuzzy number, and interval-valued intuitionistic fuzzy number. During the process of algorithm construction, the evaluation information at all time episodes is firstly aggregated into one, and then it is transformed into the unified interval-valued intuitionistic fuzzy number representational form. Similar to most multicriteria decision making approaches, the TOPSIS method is applied in the proposed decision making algorithm. In particular, the distance between possible patterns and the ideal solutions is defined in terms of cosine similarity by considering all aspects of the unified evaluation information. Experimental results show that the proposed decision making approach can effectively select desirable pattern(s).

Sign in / Sign up

Export Citation Format

Share Document