Abstract: Over the past decades, amount of scientific information has been growing exponentially. It became more complicated to process and systemize this amount of data. The approach to systematization of scientific information on the production of biogas based on the ontological IT platform “T.O.D.O.S.” has been developed. It has been proposed to select semantic characteristics of each work for their further introduction into the IT platform “T.O.D.O.S.”. An ontological graph with a ranking function for previous scientific research and for a system of selection of microorganisms has been worked out. These systems provide high performance of information management of scientific information.
Abstract: A bi-objective fuzzy transportation problem with the objectives to minimize the total fuzzy cost and fuzzy time of transportation without according priorities to them is considered. To the best of our knowledge, there is no method in the literature to find efficient solutions of the bi-objective transportation problem under uncertainty. In this paper, a bi-objective transportation problem in an uncertain environment has been formulated. An algorithm has been proposed to find efficient solutions of the bi-objective transportation problem under uncertainty. The proposed algorithm avoids the degeneracy and gives the optimal solution faster than other existing algorithms for the given uncertain transportation problem.
Abstract: Ranking of fuzzy numbers play an important role in
decision making, optimization, forecasting etc. Fuzzy numbers must
be ranked before an action is taken by a decision maker. In this
paper, with the help of several counter examples it is proved that
ranking method proposed by Chen and Chen (Expert Systems with
Applications 36 (2009) 6833-6842) is incorrect. The main aim of this
paper is to propose a new approach for the ranking of generalized
trapezoidal fuzzy numbers. The main advantage of the proposed
approach is that the proposed approach provide the correct ordering
of generalized and normal trapezoidal fuzzy numbers and also the
proposed approach is very simple and easy to apply in the real life
problems. It is shown that proposed ranking function satisfies all
the reasonable properties of fuzzy quantities proposed by Wang and
Kerre (Fuzzy Sets and Systems 118 (2001) 375-385).
Abstract: In this paper, a new method is proposed to find the fuzzy optimal solution of fuzzy assignment problems by representing all the parameters as triangular fuzzy numbers. The advantages of the pro-posed method are also discussed. To illustrate the proposed method a fuzzy assignment problem is solved by using the proposed method and the obtained results are discussed. The proposed method is easy to understand and to apply for finding the fuzzy optimal solution of fuzzy assignment problems occurring in real life situations.
Abstract: In the proposed method for Web page-ranking, a
novel theoretic model is introduced and tested by examples of order
relationships among IP addresses. Ranking is induced using a
convexity feature, which is learned according to these examples
using a self-organizing procedure. We consider the problem of selforganizing
learning from IP data to be represented by a semi-random
convex polygon procedure, in which the vertices correspond to IP
addresses. Based on recent developments in our regularization
theory for convex polygons and corresponding Euclidean distance
based methods for classification, we develop an algorithmic
framework for learning ranking functions based on a Computational
Geometric Theory. We show that our algorithm is generic, and
present experimental results explaining the potential of our approach.
In addition, we explain the generality of our approach by showing its
possible use as a visualization tool for data obtained from diverse
domains, such as Public Administration and Education.
Abstract: Fuzzy linear programming is an application of fuzzy set theory in linear decision making problems and most of these problems are related to linear programming with fuzzy variables. A convenient method for solving these problems is based on using of auxiliary problem. In this paper a new method for solving fuzzy variable linear programming problems directly using linear ranking functions is proposed. This method uses simplex tableau which is used for solving linear programming problems in crisp environment before.
Abstract: In this paper, the fuzzy linear programming formulation
of fuzzy maximal flow problems are proposed and on the basis of the
proposed formulation a method is proposed to find the fuzzy optimal
solution of fuzzy maximal flow problems. In the proposed method all
the parameters are represented by triangular fuzzy numbers. By using
the proposed method the fuzzy optimal solution of fuzzy maximal
flow problems can be easily obtained. To illustrate the proposed
method a numerical example is solved and the obtained results are
discussed.