A new lexicographical approach for ranking fuzzy numbers

In the literature many ranking methods have been proposed for comparing the fuzzy numbers, most of them suffer from plenty of shortcomings such as complex calculations, inconsistency with human intuition. To overcome such shortcomings, a new ranking method is proposed for L-R flat fuzzy numbers which is based on the lexicographical ordering approach. It is shown that proposed ranking method satisfies all the reasonable properties of the ordering fuzzy quantities proposed by Wang & Kerre (Fuzzy Sets and Systems 118(2001) 375-385). Finally a comprehensive comparison is done between the existing ranking methods with the proposed one to demonstrate the effectiveness of the proposed ranking method. Keywords: Ranking method, L-R flat fuzzy number

ON SINGLE OBJECTIVE LINEAR MODEL IN CONTROLLING COMMUNICABLE DISEASES BASED ON FUZZY LINEAR PROGRAMMING PROBLEM

Fuzzy Single objective optimization is the process of optimizing systematically and simultaneously a collection of objective functions with fuzzy variable. In this paper, fuzzy single objective linear model is developed based on fuzzy linear programming to minimize the overall treatment cost, curing time and dosage of medicine by distributing the various treatments to the disease population in order to minimize the human productivity loss. This model will help to the health department in controlling the communicable diseases with minimum cost, time and dosage of medicine

FUZZY OPTIMIZATION MODELING IN THE ANALYSIS OF HUMAN HEALTH CARE BASED ON LINEAR PROGRAMMING PROBLEM

Communicable diseases are the diseases which can be spread from one person to the other. It can also spread from infected animals. The transfer of the infection can occur through air, water, surfaces which are contaminated or through the direct contact. Moreover, Communicable Diseases are common among people nowadays days. In this paper, Fuzzy Optimization Model is developed based on Linear Programming Problem to control the communicable diseases with minimum curing time and dosage by distributing the various treatments to the disease population in order to reduce the human productivity loss. Finally, to demonstrate the feasibility of the proposed optimization model, an analytic technique is given for some four combinable diseases with four types of treatments

Investors’ preference order of fuzzy numbers

AbstractNowadays greater and greater realistic financial problems are modeled by using the stochastic programming in the fuzzy environment. Hence, ranking a set of fuzzy numbers that is consistent with the investors’ preference becomes important for modelling a realistic problem. In this paper, we will provide a new ranking procedure that is consistent with the preference of the conservative investors. Our ranking procedure satisfies the axioms of three order relations for the separable fuzzy numbers or the triangle fuzzy numbers. We found that our ranking procedure has a better capability of discriminating the order of two fuzzy numbers. For the LR-type fuzzy numbers, our ranking procedure reduces the computational time substantially

Stable Frank-Kasper phases of self-assembled, soft matter spheres

Single molecular species can self-assemble into Frank Kasper (FK) phases, finite approximants of dodecagonal quasicrystals, defying intuitive notions that thermodynamic ground states are maximally symmetric. FK phases are speculated to emerge as the minimal-distortional packings of space-filling spherical domains, but a precise quantitation of this distortion and how it affects assembly thermodynamics remains ambiguous. We use two complementary approaches to demonstrate that the principles driving FK lattice formation in diblock copolymers emerge directly from the strong-stretching theory of spherical domains, in which minimal inter-block area competes with minimal stretching of space-filling chains. The relative stability of FK lattices is studied first using a diblock foam model with unconstrained particle volumes and shapes, which correctly predicts not only the equilibrium {\sigma} lattice, but also the unequal volumes of the equilibrium domains. We then provide a molecular interpretation for these results via self-consistent field theory, illuminating how molecular stiffness regulates the coupling between intra-domain chain configurations and the asymmetry of local packing. These findings shed new light on the role of volume exchange on the formation of distinct FK phases in copolymers, and suggest a paradigm for formation of FK phases in soft matter systems in which unequal domain volumes are selected by the thermodynamic competition between distinct measures of shape asymmetry.Comment: 40 pages, 22 figure

Prediction of functionally important residues in globular proteins from unusual central distances of amino acids

<p>Abstract</p> <p>Background</p> <p>Well-performing automated protein function recognition approaches usually comprise several complementary techniques. Beside constructing better consensus, their predictive power can be improved by either adding or refining independent modules that explore orthogonal features of proteins. In this work, we demonstrated how the exploration of global atomic distributions can be used to indicate functionally important residues.</p> <p>Results</p> <p>Using a set of carefully selected globular proteins, we parametrized continuous probability density functions describing preferred central distances of individual protein atoms. Relative preferred burials were estimated using mixture models of radial density functions dependent on the amino acid composition of a protein under consideration. The unexpectedness of extraordinary locations of atoms was evaluated in the information-theoretic manner and used directly for the identification of key amino acids. In the validation study, we tested capabilities of a tool built upon our approach, called SurpResi, by searching for binding sites interacting with ligands. The tool indicated multiple candidate sites achieving success rates comparable to several geometric methods. We also showed that the unexpectedness is a property of regions involved in protein-protein interactions, and thus can be used for the ranking of protein docking predictions. The computational approach implemented in this work is freely available via a Web interface at <url>http://www.bioinformatics.org/surpresi</url>.</p> <p>Conclusions</p> <p>Probabilistic analysis of atomic central distances in globular proteins is capable of capturing distinct orientational preferences of amino acids as resulting from different sizes, charges and hydrophobic characters of their side chains. When idealized spatial preferences can be inferred from the sole amino acid composition of a protein, residues located in hydrophobically unfavorable environments can be easily detected. Such residues turn out to be often directly involved in binding ligands or interfacing with other proteins.</p

An improvised similarity measure for generalized fuzzy numbers

Similarity measure between two fuzzy sets is an important tool for comparing various characteristics of the fuzzy sets. It is a preferred approach as compared to distance methods as the defuzzification process in obtaining the distance between fuzzy sets will incur loss of information. Many similarity measures have been introduced but most of them are not capable to discriminate certain type of fuzzy numbers. In this paper, an improvised similarity measure for generalized fuzzy numbers that incorporate several essential features is proposed. The features under consideration are geometric mean averaging, Hausdorff distance, distance between elements, distance between center of gravity and the Jaccard index. The new similarity measure is validated using some benchmark sample sets. The proposed similarity measure is found to be consistent with other existing methods with an advantage of able to solve some discriminant problems that other methods cannot. Analysis of the advantages of the improvised similarity measure is presented and discussed. The proposed similarity measure can be incorporated in decision making procedure with fuzzy environment for ranking purposes

Application of Fuzzy Expert Systems to Manage the Projects Time in Iranian Gas Refineries

The National Iranian Gas Company (NIGC) is one of the top ten gas companies in the gas industry in the Middle East and is comprised of 7 gas refineries. So this company needs to apply the most optimum time management methods to achieve its goals. Custom scheduling calculation of project planning uses the Critical Path Method (CPM) as a tool for Planning Projects activities. CPM is now widely used in planning and managing projects but in spite of its wide application, this method has a critical weak point of not taking into account the uncertainties in scheduling calculation. This article aims to present a precise method based on the application of Fuzzy Expert Systems in order to improve the Time Estimation Method in construction projects and in this regard, reviews the results of the implementation of this method in construction projects of Iranian Gas Refineries. The results show that the proposed method increases the accuracy of time estimation about 7 to 22 percent

Evaluation of Leanness, Agility and Leagility Extent in Industrial Supply Chain

The focus of Lean Manufacturing (LM) is the cost reduction by eliminating non value added activities (waste i.e. muda) and enabling continuous improvement; whereas, Agile Manufacturing (AM) is an approach which is mainly focused on satisfying the needs of customers while maintaining high standards of quality and controlling the overall costs involved in the production of a particular product. This approach has geared towards companies working in a highly turbulent as well as competitive business environment, where small variations in performance and product delivery can make a huge difference in the long term to a company’s survival and reputation amongst the customers. Leagility is basically the aggregation of lean and agile principles within a total supply chain strategy by effectively positioning the decoupling point, consequently to best suit the need for quick responding to a volatile demand downstream yet providing a level scheduling upstream from the marketplace. A leagile system adapts the characteristics of both lean and agile systems, acting together in order to exploit market opportunities in a cost-efficient way. The present research aims to highlight how these lean, agile as well as leagile paradigms may be adapted according to particular marketplace requirements. Obviously, these strategies are distinctly different, since in the first case, the market winner is cost; whereas, in the second case, the market winner is the availability. Agile supply chains are required to be market sensitive and hence nimble. This means that the definition of waste is different from that appropriate to lean supply. The proper location of decoupling point for material flow and information flow enables a hybrid supply chain to be better engineered. This encourages lean (efficient) supply upstream and agile (effective) supply downstream, thus bringing together the best of both paradigms. While implementing leanness/agility/leagility philosophy in industrial supply chain in appropriate situations, estimation of a unique quantitative performance metric (evaluation index) is felt indeed necessary. Such an index can help the industries to examine existing performance level of leanness/agility/leagility driven supply chain; to compare ongoing performance extent to thedesired/expected one and to benchmark best practices of lean/agile/leagile manufacturing/supply chain, wherever applicable. The present research attempts to assess the extent of leanness, agility as well as leagility, respectively, for an organizational supply chain using fuzzy/grey based Multi- Criteria Decision Making (MCDM) approaches. During this research, different