Applied Mathematics and Computational Intelligence

Recently, J. Calallero (Fixed Point Theory and Applications 2012, 2012:231) observed best proximity results for Geraghty-contractions by using the P-property. In this paper we introduce the notion of Boyd and wong result and Generalized weakly contractive mapping and show the existence and uniqueness of the best proximity point of such contractions in the setting of a metric space.

The given work is dedicated to the solving of important scientific and technical problem of forming of the method of the optimal (in mean-square sense) extrapolation of the realizations of vector random sequences for the accidental quantity of the known values used for prognosis and for various order of nonlinear stochastic relations. Prognostic model is synthesized on the basis of polynomial degree canonical expansion of vector random sequence. The formula for the determination of the mean-square error of the extrapolation which allows us to estimate the accuracy of the solving of the prognostication problem with the help of the introduced method is obtained. The block diagrams of the algorithms of the determination of the parameters of the introduced method are also presented in the work. Taking into account the recurrent character of the processes of the estimation of the future values of the investigated sequence the method is quite simple in calculating respect. The introduced method of extrapolation as well as the vector canonical expansion assumed as its basis doesn’t put any essential limitations on the class of prognosticated random sequences (linearity, Markovian property, stationarity, scalarity, monotony etc.).

In engineering applications, pure metals are rarely used because the application may require a material with different properties that is hard as well as ductile. The functionally graded materials are the materials obtained from the composition of two or more different materials, different in properties from the constituent material, to enhance the strength of the resultant material. The concept was introduced in Japan during a space plane project in 1984. Since then, a lot of research work has done in this area under various profiles and under various conditions.

In this paper, the study of the behaviour of variation of Young’s modulus is studied against radii. The axisymmetric case is considered in which the Young’s modulus is a function of radial co-ordinate only. The radial and circumferential stresses are calculated for different radii ratio and with the parametric change in Young’s modulus. An analytical solution for stresses is developed and the results are compared with those available in literature.

This paper deals with the investigations of an interaction between magnetic driver and ferromagnetic surface based on the calculation of magnetic field parameters in conditions of various thicknesses of layer. Special attention is paid for development of mathematical model of magnetic field penetration through flat soft magnetic layer. Applied aspects of developed mathematical model implementation in robotics, automation of different technological processes, renewable energy equipment and other industrial devices are discussed in the paper in details.

This paper deals with the analytical study of stress analysis and effect of variable thickness with variation in Young’s modulus and constant Poisson ratio of Pressurized Functionally Graded Rotating Discs. In another case, the functionally graded material with constant thickness and variable Poisson ratio is studied, so that the effects of Poisson ration can be analyzed. Stress analysis has been done on the rotating discs of constant thickness as well as the varying thickness and it comes out that variable thickness discs perform better than constant thickness with varying Poisson’s ration as it shows a significant decrease in stresses.

The concept of obtaining fuzzy sum of fuzzy colorings problem has a novel application in scheduling theory. The problem of scheduling N jobs on a single machine and obtaining the minimum value of the job completion times is equivalent to finding the fuzzy chromatic sum of the fuzzy graph modeled for this problem. In the present paper the task scheduling problem is solved by using fuzzy graph.

This paper introduces SmartMonkey, a novel web-browser approach for solving NP-hard combinatorial optimization problems in “real time” (usually a few seconds). Our approach makes use of randomized algorithms that are run in parallel on a set of independent machines available on the Internet. These machines do not need to be configured, and no client application needs to be installed on them. Instead, just by opening a web page in a web browser, the computational resources of the machine become available for the algorithms to be executed. Being a configuration-free approach, it offers a great advantage to end users, since they are relieved from the usually complex and time-consuming configuration tasks that characterize other distributed-computing approaches. Computational tests have been carried out using different algorithms for solving NP-hard combinatorial optimization problems in transportation and production scheduling. The results show that our approach allows obtaining near-optimal solutions in real time, which can be especially interesting for supporting decision-making processes, especially those in small and medium enterprises, in a wide range of application fields including logistics, transportation, smart cities, and manufacturing.

In this paper authors present new universally applicable analytical models of the result’s MFs with the description of synthesis procedures for the subtraction operation with triangular fuzzy numbers and various shapes of MFs. The general soft computing analytic models are given based on the developed library consisting of the 16 general resulting models. Specific properties of the developed soft computing models are discussed with interpretation to ship bunkering problem.

In this work the current state of the problem, which consists in choice the rational model of academic-industry interaction such as “University – IT-company” is analyzed. To solve this problem it is developed and researched the intelligent decision support system (DSS) based on fuzzy logic for multi-criterion evaluation the most rational model of academic-industry interaction such as “University – IT-company” in case of changing dimension of input coordinates vector.

This paper presents a four-step metaheuristic for addressing a rich and real-life vehicle routing problem. A set of customers request several products that must be delivered using a heterogeneous fleet of trucks with different compartments (one per product). These vehicles depart from a set of depots, which do not have enough capacity for meeting the aggregated customers’ demand of products. Therefore, some vehicles must visit an external facility at the beginning of their routes in order to obtain the necessary products to deliver. A real-world case has been solved, providing savings in reduced computing times.

In this paper, an extension of OWA-TOPSIS model by inclusion of a concept of majority opinion and generalized aggregation operators for group decision making is proposed. To achieve this objective, two fusion schemes in TOPSIS model are designed. First, an external fusion scheme to aggregate the experts’ judgments with respect to the concept of majority opinion on each criterion is proposed. Then, an internal fusion scheme of ideal and anti-ideal solutions that represents the majority of experts is proposed using the Minkowski OWA distance with the inclusion of relative importances of criteria. The advantages of the proposed model include, a consideration of soft majority concept as a group aggregator and a flexibility in applying the decision strategies for analyzing the decision making process. In addition, instead of calculate the majority opinion with respect to the individual experts’ judgments on each alternative, the proposed method takes into account the majority of experts on each criterion, in which reflects the specificity on criteria for overall decision. A numerical example is provided to demonstrate the applicability of the proposed method and comparisons are made between some aggregation operators and distance measures.

In this paper we propose to apply fuzzy logic methodologies for measuring key performance indicator into Balanced Scorecard (BSC) Customer Perspective. This study provide fuzzy key performance indicator (FKPI) to the customer experience management for uncertainty measures. The proposal is a step forward in terms of methodologies for creation of performance indicators in the field of marketing, where you have the opportunity to work with uncertain or vague data (human language). The significant contribution of the research is include qualitative data indicator, result from analysis the information that expresses the client in text format, to BSC. The methodology used is the model proposed by Mamdani fuzzy inference which is based on the fuzzy logic theory and fuzzy subsets. Software Matlab was used for the analysis.

In the area of Fuzzy Operational Research, fuzzy transportation problem and fuzzy assignment problem were dealt with by several authors using a variety of fuzzy real numbers that are listed in the literature survey in [4, 5], wherein the problems are handled by converting them to be crisp case. Unlike in the case of real numbers, fuzzy numbers have no natural order. As a consequence, there are several ranking methods in literature [1, 2, 7] to compare or/and rank fuzzy numbers introduced by various authors since 1976. Based on the context of the application, some methods seem to be more appropriate than others.

The concept of octagonal fuzzy numbers and a ranking procedure using their α-cuts was introduced by the authors in an earlier paper [4]. Also the concept on symmetric octagonal fuzzy numbers has been introduced by the authors in [3]. The parameter ‘\( k \)’, \( 0 \le k \le 1 \) involved in the definition of octagonal fuzzy numbers may be chosen appropriately to suit the situation/problem.

In this paper, symmetric octagonal fuzzy numbers are used to solve fuzzy transportation problem and fuzzy assignment problem, as distributive property holds only in the case of symmetric octagonal fuzzy numbers. New methods to solve the fuzzy transportation problem and fuzzy assignment problem are proposed in Sects. 4 and 5 respectively. Both the problems are solved without converting them to crisp problems. The solution procedures are illustrated with numerical examples.

In this chapter, we consider a mixed-integer bilevel linear programming problem with one parameter in the right-hand side of the constraints in the lower level (or, the follower’s) problem. Motivated by an application to the fuzzy portfolio optimization model, we consider a particular case that consists in maximizing the investor’s expected return. The functions are linear at both the upper and lower levels, and the proposed algorithm is based upon an approximation of the optimal value function using the branch-and-bound method. Therefore, at every node of this tree-type structure, we apply a new branch-and-bound procedure to deal with the integrity restriction.

In this paper, an analysis on extensions of multi-expert decision making model based on ordered weighted averaging (OWA) operators is presented. The focus is on the aggregation of criteria and the aggregation of individual judgment of experts. First, soft majority concept based on induced OWA (IOWA) and generalized quantifiers to aggregate the experts’ judgments is analyzed, in which concentrated on both classical and alternative schemes of decision making model. Secondly, analysis on the weighting methods related to unification of weighted average (WA) and OWA is conducted. An alternative weighting technique is proposed which is termed as alternative OWA-WA (AOWAWA) operator. The multi-expert decision making model then is developed based on both aggregation processes and a comparison is made to see the effect of different schemes for the fusion of soft majority opinions of experts and distinct weighting techniques in aggregating the criteria. A numerical example in the selection of investment strategy is provided for the comparison purpose.

The Staff Planning process, which has the responsibility to provide for the needs of workforce, must be borne by the companies as a key process sin the sub-heading Human Resources (HR). The Theory of Fuzzy Subsets is shown as a tool to help decision-making in this field. This paper proposes a method for Staff Planning based on the Theory of Fuzzy Subsets, to help decrease this subjectivity and ensure precise and accurate results as well assist application in the company SERVICEX.

Financial markets are connected well these days. One class assets’ price performance is usually affected by movements of other classes of assets. The liquidity conduction mechanism usually is: if capital surface of money market is tight, investors may dump short-term treasury bonds to exchange additional liquidities. It may affects the performance of treasury bonds’ yield of maturity. Credit bonds’ return rate thus will level up hysteretic. Financing cost of companies accordingly raise, then throws effects on their stock prices. However, situation changes along with increase in complexity of markets’ behaviors these days. In order to model movements of assets’ price performance, analysis of linkage between different markets is thus becoming more and more important. Nothing like stock market, money market or bond market is an over-the-counter market, where assets’ prices are often presented in the form of classes of discrete quotations with trader’s subjective judgements, thus are hard to analyze. Given concern to this, we define the Type 2 fuzzy random variable (T2 fuzzy random variable) to quantify those bid/offer behaviours in this paper. Moreover, we build a T2 fuzzy random support vector regression scheme to study relationships between these markets. T2 fuzzy random support vector regression is developed from traditional support vector regression and is able to cope with fuzzy data, which has less computation complexity and better generalization performance than linear algorithms.

The Location Routing Problem (LRP) is one of the most important challenging problems in supply chain design since it includes all decision levels in operations management. Due to its complexity, heuristics approaches seem to be the right choice to solve it. In this paper we introduce a simple but powerful approach based on biased randomization techniques to tackle the capacitated version of the LRP. Preliminary tests show that near-optimal or near-BKS can be found in a very short time.

This paper describes an efficient heuristic to solve the Waste Collection Problem (WCP), which is formulated as a special instance of the well-known Vehicle Routing Problem (VRP). Our approach makes use of a biased-randomized version of a savings-based heuristic. The proposed procedure is tested against a set of benchmark instances, obtaining competitive results.

In recent decades, innovation has been recognized as one of the main sources of competitive advantage for organizations at an international level. Recently, numerous studies have been developed, mainly focused on the analyses of innovation processes in large companies, however, little has been done in the identification of innovative capabilities that allow small and medium-sized companies to compete in highly uncertain environments. This study presents the interpreted results of an innovation diagnosis utilizing the Experton method and the application of the generalized ordered weighted average operator (GOWA) for the treatment of information. The focus relies on seven organizational areas of small and medium-sized manufacturing companies. The applied questionnaire presents 32 exploration and 5 control questions applied to a total of 217 small and medium-sized companies in the Latin American city of Morelia, Mexico. The present work seeks to shed light in the diagnosis of innovation capabilities in manufacturing companies with the aim of fostering synergies and effectively allocate resources for the promotion of innovation management as a source of competitiveness and economic growth.

We coped with association rule-based modal data analysis, and generated rules by using the getRNIA software tool. This tool is powered by the NIS-Apriori algorithm, and handles tables with non-deterministic information. Moreover, the NIS-Apriori algorithm is logically complete for the defined rules. In this paper, we consider the NIS-Apriori algorithm with the granules defined by the descriptors. By using these granules, we can uniformly apply NIS-Apriori algorithm to various types of uncertain data sets. The problem is reduced to the definition of the descriptors and the granules. We show the property of this algorithm and some examples.

Facility Location Problems (FLPs) have been widely studied in the fields of Operations Research and Computer Science. This is due to the fact that FLPs have numerous practical applications in different areas, from logistics (e.g., placement of distribution or retailing centers) to Internet computing (e.g., placement of cloud-service servers on a distributed network). In this paper we propose a biased iterated local search algorithm for solving the uncapacitated version of the FLP. Biased randomization of heuristics has been successfully applied in the past to solve other combinatorial optimization problems in logistics, transportation, and production -e.g., different vehicle and arc routing problems as well as scheduling problems. Our approach integrates a biased randomization within an Iterated Local Search framework. Several standard benchmarks from the literature have been used to prove the quality and efficiency of the proposed algorithm.

Academic research in gender payment gaps and woman’s economic behavior has been developing over the last decades. The European Project itself edifies on the Lisbon Treaty’s values of respect for human dignity, freedom, equality, etc. Therefore important contributions have been published in the main journals of the field of economic and social research. This paper analyzes the results of the research concerning woman’s work culture in all economic fields by using bibliometric indicators. The main results are summarized in two fundamental issues. First, the citation structure, in economics and social sciences, is presented. Next, the paper studies the influence of the journals by using a wide range of indicators including publications, citations and the h-index. There is found the results are in accordance with the expectations, that the research on the woman’s economic role is very narrow and needs to be enriched with scholar further researches.

Asian academic research in tourism is a very recent field of research, which has significantly developed over the last decade due to the strong expansion of the tourism industry worldwide, and also owing to the strong evolution of search engines via the Internet. This article analyses the main contributions to Asian academic research in tourism over recent years using bibliometric indicators. The results obtained are based on the information contained in the Web of Science database. These results focus on explaining three fundamental questions. Firstly, we study the publication structure of Asian articles in tourism over recent decades, as well as the citations these articles have received. Secondly, we present a ranking of the most important tourism journals in Asia through the use of a series of indicators such as the number of publications in said journals, the number of citations, and the h-index. Finally, we present a list of the 50 most cited Asian articles in tourism (and hence the ones that can be considered the most influential) of all times. The results show how, in Asian terms, the most influential journals in this field are Tourism Management (TM), the Annals of Tourism Research (ATR) and the International Journal of Hospitality Management (IJHM).

Bibliometrics is a fundamental field of information science that helps to draw quantitative conclusions about bibliographic material. During the last decade, the use of techniques and bibliometric studies has experienced a significant increase due to the improvement of information technology and its usefulness to organize knowledge in a scientific discipline. This paper presents an overview of the most productive and influential Asian universities and countries in academic tourism research through the use of bibliometric indicators, according to information found in the database Web of Science (WoS). This database is considered one of the main tools for the analysis of scientific information. In order to analyze the information obtained, several rankings of universities and countries have been carried out, both global and individual, based on a series of bibliometric indicators, such as the number of publications, the number of citations and h-index. Analyzing the results, we observe that within tourism research in Asia, the most influential countries are China, Taiwan and South Korea, and that the leading university is Hong Kong Polytechnic University.

The main purpose of this article is to reflect the extent of the scientific research done about two important concepts as the managerial culture and the knowledge based society, in the last two decades, in the areas of business economics and management, by the method of the bibliometric research. Bibliometry is broadly used today to assess the state of the art of a research subject, as the ease of access to scientific information via internet enabled this.

A sound literature review allows us to delimit the field of the research, for the more precise goal of finding the correlations between the managerial culture and the knowledge society achievement. The papers presents, as main findings, the scientific interest shown in the last two decades for this two concepts, using bibliometric indicators such as number of published items, number of citations received by an article or in a journal, ranking of journals and H-index. Following, we found that there are potential determinations between the two concepts, which are suggested by the results of the bibliometric assessment of the theme.

The aim of the paper is to examine the stakeholder dynamics through causality relationship process. The study proposes a methodological perspective of stakeholders, which allows analysing the linking of relationship from the relative intensity and linked relations of entire stakeholders. An application is developed to help decision-making process in uncertainty concerning the ordering according to their importance algorithm and linking of relation method, which are based on notions of relation, gather and order. The case of study is focused on The Family Compensation Funds (FCF) in Colombia. The results show how the ambiguity and fuzziness of the stakeholders and appraisal subjective of decision-maker can be dealt with, helping to make a decision according to its individual estimations. The linked relations between each stakeholders and relative intensity are depicted. As the ties relations of incidence and relative impact on stakeholder behaviours are explained. The main implication of this proposition is to enable to deal with the subjective appraisal of the decision-maker to do a better interpretation of environment and subjectivity factors. Furthermore, it contributes to aid to the strategic planning and decision-making process for operative unit within uncertainty environment in the short-term.

Based on the geometry of finite projective planes, a secret-key encryption scheme which offers an exactly computable degree of secrecy is described. This target is achieved at the cost of an encryption rate equal to \(\frac{1}{2}\), as in one-time-pad encryption, but the devised scheme avoids the burden of exchanging and destroying long keys. It is also shown that knowledge of pieces of plain text does not significantly reduce the degree of secrecy; further, the cost of possible plain-text attacks is under the designer’s control, and can be made as high as desired.

When investors apply foreign exchange options to avoid foreign exchange risk, the key issue is how to use a reasonable mathematical model to determine the price of foreign exchange options. At present, volatility is mostly determined by using subjective estimations and sample calculations. Therefore, different sources of volatility result in large differences between calculated price and the actual price of the exchange options, which will affect the strategy selection and the actual return of investors. Meanwhile, in the actual foreign exchange market, the normal distribution-based return rate cannot express the fat tail situation of volatility. This paper clarifies the inverse problem based on the fat tail of return rates of foreign exchange in option pricing. The inverse problem plays a pivotal role in determining the form of implied volatility and fluctuations in the value scope. First, this paper summarizes the present state of research on the inverse problems of foreign exchange option pricing. Second, this paper explains the basic theory of foreign exchange options, and deduce a positive foreign exchange option pricing problem, that is, G-K foreign exchange option pricing. At the same time, it proposes the inverse problem of foreign exchange option pricing, then puts forward a foreign exchange option pricing model based on the t-distribution and the inverse problem which is more appropriate to the actual foreign exchange market. Last the paper exemplifies the foreign exchange option pricing inverse problem based on fat tail of exchange rate return by using the numerical differential algorithm, which solves implied volatility.