The paper discusses some core topics which present open problems in the field of mathematical fuzzy logic and in the foundations of fuzzy set theory. It may reasonably be assumed that these problems shall have great influence for the future development of fuzzy logic within the next decade.
In present issue the technique of adequate precise valuations of financial parameters of the investment based on the method of multiobjective optimization in the case of initial data presented as the fuzzy-intervals is offered. The final results obtained as the compromise between criteria of a profit maximization and minimization of financial risk.
The Fuzzy SERVQUAL method enables to assess the service quality when the measurement results of the performance perception and expectations are expressed in the form of fuzzy numbers. The measurement results expressed in the form of fuzzy numbers are the results of applying the fuzzy conversion scales which are the most popular form of fuzzy scales. Fuzzy conversion scales assume that their points are expressed in the form of fuzzy numbers. The choice of fuzzy number parameters which describe the various points of measurement scales is most often subjective. The aim of the article is to assess the impact of the choice of the fuzzy conversion scale on the stability of the assessment results of the ser-vice quality using the fuzzy SERVQUAL method. The stability assessment was made both for the individual dimensions and the overall SERVQUAL score. The results of employee satisfaction surveys of the West Pomeranian Province local government were used for the purpose of the assessment. The results suggest that there is no significant impact of the form of fuzzy conversion scales on the stability of the assessment results of the service quality us-ing the fuzzy SERVQUAL method.
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In this article, we continue the development of the theory of fuzzy sets [23], started with [14] with the future aim to provide the formalization of fuzzy numbers [8] in terms reflecting the current state of the Mizar Mathematical Library. Note that in order to have more usable approach in [14], we revised that article as well; some of the ideas were described in [12]. As we can actually understand fuzzy sets just as their membership functions (via the equality of membership function and their set-theoretic counterpart), all the calculations are much simpler. To test our newly proposed approach, we give the notions of (normal) triangular and trapezoidal fuzzy sets as the examples of concrete fuzzy objects. Also -cuts, the core of a fuzzy set, and normalized fuzzy sets were defined. Main technical obstacle was to prove continuity of the glued maps, and in fact we did this not through its topological counterpart, but extensively reusing properties of the real line (with loss of generality of the approach, though), because we aim at formalizing fuzzy numbers in our future submissions, as well as merging with rough set approach as introduced in [13] and [11]. Our base for formalization was [9] and [10].
Purpose: Summarize the experience of using modern methods in the business plan with the application of economic and mathematical modeling. Methodology: Theoretical and methodological basis of the study is the basic principles of economic theory, agricultural economics and scientific research of leading home and foreign scholars on the theory of planning. Originality: This further justifies business planning processes in agriculture from the standpoint of raising economic protection of farmers. The methodology for assessing farm income for planned indicators through the application of fuzzy numbers method in business planning is improved.
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When dealing with multi-criteria decision making problems, the concept of Pareto-optimality and Pareto-dominance may be inefficient (e.g. generally multiple solutions exist), especially when there is a large number of criteria. Our paper considers the fuzzy multi-criteria decision making problem based on Zadeh’s linguistic approach to P-optimality and P-dominance. The construction, analysis and application of a model of multi-criteria decision making using a fuzzy preference relation are considered. The paper is dedicated to the problem of modeling preferences in terms of fuzzy binary relations and provides an introduction to the important problem of forming fuzzy preference relations to analyze models of multi-attribute decision making. The key features of the multi-criteria evaluation, comparison, choice and ordering of alternatives in a fuzzy environment using fuzzy preferencerelations have been introduced.
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An industrial gauge for measuring thickness of a gold coating layer deposited on a steel base through detection of the backscattered beta particles has been described. 3H, 14C and 63Ni pure beta emitters have been tested as the radioisotopic sources of the system individually in a fixed geometry. Analytical calculations have been performed in each case. Furthermore, simulations based on Monte Carlo stochastic technique (MCNP) have been processed. The obtained results from both methods have been compared to define the sensitivity of the system in each case. Finally for the first time, fuzzy TOPSIS method has been used for choosing the best source in the defined geometry for manufacturing, considering the following three criteria: (a) saturation thickness, (b) precision and (c) sensitivity. Results have shown that 3H source is the best alternative to the introduced measuring system.
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The paper presents a proposal of a new methodology that evaluates multicast routing algorithms in packet-switched networks with an application of fuzzy sets. Proposed multicriteria mechanism evaluate representative multicast routing algorithms: KPP, CSPT and MLRA (Multicast Routing Algorithm with Lagrange Relaxation) that minimize cost of paths between source and each destination node using Lagrange relaxation, and finally, minimize the total cost of multicast tree. A wide range of simulation research carried out by the authors, confirmed both the accuracy of new methodology and the effectiveness of the MLRA algorithm proposed by authors in earlier works.
W referacie przyjęto założenie, że rozkład możliwych terminów realizacji dostaw materiałów budowlanych i preferowane terminy ich przyjęcia na placu budowy sąmodelowane przez liczby rozmyte. Przedstawiono metodę analityczną oceny synchronizacji dostaw i zapotrzebowania na materiały budowlane z wykorzystaniem koncepcji α-przekrojów liczby rozmytej. Zastosowanie metody zilustrowano na przykładzie liczbowym.
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The paper assumes that spread of possible delivery time of building materials and theirs preferable delivery schedule on building site are projected by fuzzy numbers. Authors presented an analytical assessment method of deliveries synchronisation and demand on building materials with use of fuzzy number’s α-sections. The use of the method has been illustrated on a mathematical example.
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We outline the relationship between classical (orthodox) sets from one side, and fuzzy and rough (non-orthodox) sets from another side. The classical concept of a set used in mathematics leads to antinomies, i.e., it is contradictory. This deficiency has, however, rather philosophical than practical meaning. Antinomies are associated with very "artificial'1 sets constructed in logic but not found in sets used in mathematics. That is why one can use mathematics safely. Fuzzy set and rough set theory are two different approaches to vagueness and are not remedy for classical set theory difficulties. Fuzzy set theory addresses graduainess of knowledge, expressed by the fuzzy membership, whereas rough set theory addresses granularity of knowledge, expressed by the indiscernibility relation. From practical point of view both theories are not competing but are rather complementary.
The article outlines how to use the convergence of collections to determine the position of a mobile device based on the WiFi radio signal strength with the use of fuzzy sets. The main aim is the development of the method for indoor position determination based on existing WiFi network infrastructure indoors. The approach is based on the WiFi radio infrastructure existing inside the buildings and requires operating mobile devices such as smartphones or tablets. An SQL database engine is also necessary as a widespread data interface. The SQL approach is not limited to the determination of the position but also to the creation of maps in which the system dening the position of the mobile device will operate. In addition, implementation issues are presented along with the distribution of the burden of performing calculations and the benets of such an approach for determining the location. The authors describe how to decompose the task of determining the position in a client-server architecture.
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This paper presents a fuzzy multi-objective decision model for a vertically integrated steel supply chain to produce and allocate scarce steel products among a set of alternative distribution channels based on their past performances. The objectives include net profits, inventory costs, backorder amounts, rate of end user claims and late lading amounts. Uncertainty in market demand and capacity is considered in the model to reflect the current steel industry environment. Using the concepts of additive criterion and preemptive priority, the proposed model generates a robust and preferred tactical plan by specifying desired satisfaction levels, demand fulfilment rates and capacity utilization according to the operations and channels management policy. We validated the model with the operational data and parameters of a major Taiwan based integrated steel manufacturer. The results show that the model can effectively handle channel focused production and allocation planning problems under uncertain industry environments.
This paper presents recent approaches in soft computing to manage imprecision and uncertainty which appear in software reliability engineering. Firstly, recent approaches like imprecise probabilities, generalized intervals, fuzzy sets and intuitionistic-fuzzy sets are shortly described, and the usage of intuitionistic fuzzy numbers for system reliability computation is shown. Intuitionistic-fuzzy approaches for software reliability growth models are proposed and experimental results are given.
In the paper the theory of fuzzy sets is discussed from the standpoint of theory, and the concept of fuzzy reliability, the fuzzy mean value of the time up to a failure and the fuzzy failure rate are defined. The mathematical method used is also specified. Subsequently, this mathematical method is applied to a data set that was acquired from three-phase asynchronous motors with identical output and construction. The motors used to acquire the data totalled 300. The motors were used in industrial practice as the drives of belt conveyers in mines or as fan drives in thermal power plant. A major part of the paper discusses the results obtained and the fuzzy reliability comparison to the standard reliability. Graphical curves are also included in the paper.
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A variety of numerical approaches for reasoning with uncertainty have been investigated in the literature. We propose rough membership functions, rm-functions for short, as a basis for such reasoning. These functions have values in the interval [0,1] and are computable on the basis of the observable information about the objects rather than on the objects themselves. We investigate properties of the rm-functions. In particular, we show that our approach is intensional with respect to the class of all information systems [P91]. As a consequence we point out some differences between the rm-functions and the fuzzy membership functions [Z65], e.g. the rm-function values for X ∪ Y (X ∩ Y) cannot be computed in general by applying the operation max(min) to the rm-function values for X and Y.
When dealing with multi-criteria decision making problems, the concept of Pareto-optimality and Pareto-dominance may be inefficient (e.g. generally multiple solutions exist), especially when there is a large number of criteria. Our paper considers the fuzzy multi-criteria decision making problem based on Zadeh’s linguistic approach to P-optimality and P-dominance. The construction, analysis and application of a model of multi-criteria decision making using a fuzzy preference relation are considered. The paper is dedicated to the problem of modeling preferences in terms of fuzzy binary relations and provides an introduction to the important problem of forming fuzzy preference relations to analyze models of multi-attribute decision making. The key features of the multi-criteria evaluation, comparison, choice and ordering of alternatives in a fuzzy environment using fuzzy preference relations have been introduced.
Decision support and trading systems for the forex market mostly derive a single signal for the decision-maker. This is so, because instruments are evaluated based on a single criterion, which creates a ranking of instruments, from which the best one is selected. At the same time, one can observe a lack of tools al- lowing one to derive the set of non-dominated trading opportunities considered in the multicriteria space. This article focuses on multicriteria analysis, in which several different market indicators describe a single instrument on the forex market (currency pair), leading to definite criteria. Thus, for a given time horizon, we consider a set of currency pairs described by a group of technical market indicators in every trading session. However, instead of deriving crisp information, based on the buy-no buy binary logic, we use concepts from the fuzzy sets theory, in which each criterion for a single variant takes a value from the h0, 1i interval. We select only the non-dominated variants from such a set, which will be used as elements of the portfolio of currency pairs on the forex market. We test our idea on the real-world data covering more than ten years, several technical market indicators, and over twenty different currency pairs. The preliminary results show that the proposed idea can be treated as a promising concept for deriving a portfolio of currency pairs instead of focusing on only a single currency pair.
Gathering reliability data is quite difficult. Potential sources of such data are: reliability guides and handbooks, data collecting during operation of technical devices, expert judgments. Practice shows that very often the statistical sample we have to our disposal is small and non – homogenous. The goal of the author was to verify, if it is possible to draw out useful in practice conclusions about reliability of technical items from small statistical sample and how to do it. In the article two potential ways to deal with the problem of small reliability data sample have been presented. First way is based on using mathematical statistics methods, the second way uses the fuzzy sets theorem methods.
The article is aimed on the possibility of fuzzy control of an experimental device that represents the simplified model of automobile steering booster. The main part of model consists of a graphical unit illustrating the control of speed and supporting torque. Based on the structure of fuzzy controller, various counts and configurations of fuzzy sets were defined, whereby the relevant results were achieved by their application on controlled system.
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