The main change compared to the classical rough sets is the substitution for the indiscernibility relation by a dominance relation, which permits one to deal with inconsistencies typical to consideration of criteria and. The original rough set approach proved to be very useful in dealing with inconsistency problems following from information granulation. Rough set theory developed by 46 is regarded as a mathematical tool for imperfect data analysis and may be applied in engineering, banking, medicine 7. In this chapter, the authors present a new strategy for multiattribute decision making in interval rough neutrosophic environment. Artificial intelligence and human decision making, european journal of operational research, elsevier, vol. It finds minimal data sets and generates a decision rule from the resulting data. A webbased software dedicated to solve multiobjective mixedinteger programs developed by. Methods and applications focuses on the fuzzy set approach to multiple attribute decision making madm. Comfor t, perf ormance, reliability,s iz e, safety,s tyle, ima ge, equipment, handling, noise,running costs. An assessment method for the impact of missing data in the rough set based decision fusion. Rough set theory proved to be a useful tool for analysis of a vague description of decision situations. The present study is mainly a continuation of our previous study, which is about a crop evaluation system development that is based on grey relational analysis.
The lower and the upper approaches are two basic functions in the rough sets theory. We propose the use of rough set theory modified by 8 and called dominancebased rough set approach drsa in portfolio management, more specifically in the man. A rough set based method for updating decision rules on attribute values coarsening and refining, ieee transactions on knowledge and data engineering, 2612. It has been created at the laboratory of intelligent decision support systems of the institute of computing science in poznan, basing on fourteenyear experience in rough set based knowledge discovery and decision analysis. In zhong n, skowron a, ohsuga s, editors, new directions in rough sets, data mining, and granularsoft computing. Rough family software implementation of rough set based data.
One of the main advantages of our application over the previous ones is the possibility of a future. Multiattribute decision making method based on rough set and evidence theory. Goals of rough set theory the main goal of the rough set analysis is the induction of learning approximations of concepts. A free decision support tool, available in german and english, with a decision front end supporting the ideas, concepts, and methods of valuefocused thinking and a decision back end based on multi attribute utility theory maut. Variable precision diversified attribute multigranulation fuzzy rough set based multiattribute group decision making problems. Drawing on their experience, the authors bring together current methods and reallife applications of madm techniques for decision analysis.
A multiattribute decision analysis method based on rough. More recent adaptations of rough set theory, such as dominancebased, decision theoretic and fuzzy rough sets, have introduced more subjectivity to the analysis. Neutrosophic set, rough neutrosophic set, singlevalued neutrosophic set, grey relational analysis, information entropy, multiattribute decision making. There are many advantages of the rough sets approach in data analysis. Rough neutrosophic topsis for multiattribute group decision making. Theory and application on deepdyve, the largest online rental service for scholarly research with thousands of academic publications available at your fingertips.
Rough sets theory for multicriteria decision analysis. An algorithm of attribute reduct based on rough set. Software related to mcdm multiple criteria decision making. Keywords raster, dominance rough set approach, multi criteria decision analysis. A survey of software packages used for rough set analysis. Multiattribute decision making manydecisions are based on other attributes than price. Rough set theory answers two basic questions related to multiattribute decision problems. First, we construct a rough group decision matrix from all dms decision matrixes on the basis of rough set theory. In this paper, four classes of multiattribute decision problems are defined. As rough group decision originates from rough set theory, it can enable. From the viewpoint of rough set theory, this approach implies to consider a pairwise comparison table, i. European journal of operational research, 1994, 72. A modified rough set approach to incomplete information. Handling missing values in rough set analysis of multi.
Rough set and rulebased multicriteria decision aiding scielo. Rough set approach to multiattribute decision analysis. Rough set approach to multiattribute choice and ranking. Slowinski, handling missing values in rough set analysis of multiattribute and multicriteria decision problems, in proceedings of the 7th international workshop on new directions in rough sets, data mining, and granularsoft computing rsfdgrc 99, a. From the viewpoint of multiattribute decision methodology, this approach allows. Interval rough neutrosophic topsis strategy for multiattribute decision making. Rough sets theory for multicriteria decision analysis request pdf. We propose an original way of applying the rough set theory to the analysis of multiattribute preference systems in the choice pa and ranking py decision problematics.
What are objects and attributes is not important here and many interpretations of these results in terms of decision situations are possible. Prediction of company acquisition in greece by means of the rough set approach, european journal of operational research, elsevier, vol. Dealing with missing data in rough set analysis of multiattribute and multicriteria decision. Coveringbased spherical fuzzy rough set model hybrid with. The aim of a multiple attribute decisionmaking madm problem is to obtain. The presented approach is aimed at handling uncertain information during the process of i. The purpose of this research is to expose the results of using dominancebased rough set approach drsa to help international organizations both nongovernmental organizations and governmental organizations define poverty, identifying economical, sociological, political and technological strategic objectives for developing countries. Defining poverty using dominancebased rough set theory. Multiple criteria decision making, multiattribute utility theory. Multiattribute decisionmaking method based on rough set. Internet addresses to freely available software implementations of these.
Several attempts have been made to employ rough set theory for decision aiding. Rough set theory was introduced by pawlak 1982, pawlak 1991. In genetic algorithm, first of all, the initial population is created. Rough set approach to multiattribute decision analysis j. A compilation of modern decision making techniques, multiple attribute decision making. This study aims to present a novel approach for determining the weights of decision makers dms based on rough group decision in multiple attribute group decision making magdm problems. Read rough approximation of pairwise comparisons described by multi. Here we will discuss other classification methods such as genetic algorithms, rough set approach, and fuzzy set approach. Rough set theoryrst, put forth by pawlak 5 offers another approach of dealing with imprecise corresponding author. Multiattribute decision analysis methods request pdf. Choosing a car, forinstance, although you might be looking in a particular price band.
In its abstract form, it is a new area of uncertainty mathematics closely related to fuzzy theory. Generalized interval neutrosophic rough sets and its. Conf on computer software and applications oxford, pp. Handling missing values in rough set analysis of multiattribute and multicriteria decision problems. Multi attribute decision making strategy on projection and. Rough set theory has been a methodology of database mining or knowledge discovery in relational databases. In this paper, we utilize rough sets theory to calculate. Multi attribute decision making strategy on projection and bidirectional projection measures of interval rough neutrosophic sets. They are algorithms whose output is a set of actions. The paper puts forward the multivariable decision tree algorithm which based on a rough set to a combination of rough sets theory and decision tree algorithm. It adds the idea of degree association membership functions to the classical set theory. Rough set theory rst is one of the data mining tools, which have many capabilities such as to minimize the size of an input data and to produce sets of decision rules from a set of data.
A new rough sets approach to evaluation of bankruptcy risk. Recently the three regions of rough sets are interpreted as regions of acceptance, rejection and deferment. Rough neutrosophic topsis for multiattribute group. The idea of genetic algorithm is derived from natural evolution. Drsa is a multiple criteria decision aiding mcda method developed by greco et al. Science and technology, general decision making decision making fuzzy sets research mathematical research multiple criteria decision making methods set theory. A robust decision analysis modeling tool dpl offers an easytouse decision modeling environment that incorporates key decision framing tools influence diagrams and decision trees with excel spreadsheets to help you enhance decision quality at your organization.
This paper presents a new approach for inducing decision trees based on variable precision rough set model. Miscellaneous classification methods tutorialspoint. Rose2 rough sets data explorer is a software implementing basic elements of the rough set theory and rule discovery techniques. In this paper, a new approach for multiattribute group decision. Science and technology, general decision making decision making decision making, group methods fuzzy sets usage group decision making set theory. Decision tables are a concise visual representation for specifying which actions to perform depending on given conditions. Multiple criteria decision making, multiattribute utility.
Attribute weight is usually ascertained by decision makers experience knowledge. Rough set theory proved to be a useful tool for analysis of a vague description of decision. In that system, the attribute weight determination affects the evaluation result directly. The dominancebased rough set approach drsa is an extension of rough set theory for multicriteria decision analysis mcda, introduced by greco, matarazzo and slowinski. It operates on a data table composed of a set u of objects actions described by a set q of attributes. This article is the last of a series of three researches. Introduction the notion of rough set theory was originally proposed by pawlak 1, 2. Rough sets theory for multicriteria decision analysis citeseerx. Rough neutrosophic multiattribute decisionmaking based. A rough set approach for determining weights of decision. Rough set analysis of multiattribute decision problems.
Rough setbased data analysis methods have been successfully applied in bioinformatics, economics and finance, medicine, multimedia, web and text mining, signal and image processing, software engineering, robotics, and engineering e. The concept of rough neutrosophic set is a powerful mathematical tool to deal with uncertainty, indeterminacy and inconsistency. Rough set based approach for inducing decision trees. Stowinski rough set approach to decision analysis application of the rough set approach to the classes of decision problems distinguished above is described in sections 4 to 7, respectively. It answers two basic questions related to multiattribute decision problems. A rapid growth of interest in rough set theory 290 and its applications can be lately seen in the number of international workshops, conferences and seminars that are either directly dedicated to rough sets, include the subject in their programs, or simply accept papers that use this approach to. Rough approximation of pairwise comparisons described by. Characterization of a set of objects in terms of attribute values. We can use rough set approach to discover structural. An assessment method for the impact of missing data in the. The er approach for multiattribute decision analysis under interval uncertainties.