There are different approaches to generate a common set of weights in DEA based on the p - distance measure. Deviation of an efficiency score derived from a CSW from target efficiency score may be related to the model and the parameter p. In this study, we try to clarify points about choosing p, model, and data set if it is necessary to produce an efficiency score with the least deviation by a CSW. Two improved linear models are developed by analyzing the result of available models. The results of the proposed models have smaller individual and overall efficiency than corresponding prior ones that It has been confirmed with numerical examples and simulation analysis.
In this research, differential quadrature radial basis functions Method is performed to a fractional order model of HIV infection of CD4+T. Here, Caputo fractional derivative is used and it is approximated by forward finite difference method. Results have been compared with the results of Laplace Adomian decomposition method (LADM), Laplace Adomian decomposition method-pade (LADM-pade), Runge-Kutta, Variational iteration method (VIM) and Variational iteration method-pade (VIM-Pade) for α_1=α_2=α_3 and residual functions have been plotted. And also approximate solutions of suggested method for different order of fractional derivatives have been shown.
In this paper, we propose some necessary conditions for convergence of Triple Accelerated Over-Relaxation (TAOR) method with respect to $M-$ coefficient matrices. The theoretical approach for the proofs is analyzed through some standard procedures in the literature. Some numerical experiments are performed to show the efficiency of our approach, and the results obtained compared favourably with those obtained through the existing methods in terms of spectral radii of their iteration matrices.
We propose a new self-starting sixth-order hybrid block linear multistep method using backward differentiation formula for direct solution of third-order differential equations with either initial conditions or boundary conditions. The method used collocation and interpolation techniques with three off-step points and five-step points, choosing power series as the basis function. The convergence of the method is established, and three numerical experiments of initial and boundary value problems are used to demonstrate the efficiency of the proposed method. The numerical results in Tables and Figures show the efficiency of the method. Furthermore, the numerical method outperformed the results from existing literature in terms of accuracy as evident in the results of absolute errors produced.
The current research approximates the unknown function based on the normalized Muntz−Legendre polynomials (NMLPs) in conjunction with a spectral method for the solution of nonlinear Fredholm and Volterra integral equations. In this method, by using operational matrices, a system of algebraic equations is derived that can be readily handled through the use of the Newton scheme. The stability, error bound, and convergence analysis of the method are discussed in detail by preparing some theorems. Several illustrative examples are provided formally to show the efficiency of the proposed method.
This paper evaluates the relative performance of open source software projects by evaluating multiple project inputs and multiple project outputs by using data envelopment analysis (DEA) model. The DEA model produces an efficiency score for each project based on project inputs and outputs. One of the important issues in data envelopment analysis is ranking DMUs. In this paper, open source software projects (OSS) are considered as decision making units which consume inputs to generate outputs. In this article, three standard Data Envelopment Analysis (DEA) models are used to evaluate the open source software projects. Also, super-efficiency model are used for ranking. Due to the inability of the models to rank projects, the AP-super efficiency model (the most important and popular method for ranking units) has been used for ranking OSS projects.The result of this research is a practical model that can be used by OSS project developers in order to evaluate the relative performance of their projects and make decision for their sources. Also, OSS projects can now be adequately ranked and evaluated according to project performance.
The present research aims to identify the factors affecting the green supply chain in the steel industry with a combined approach. The research is an applied study in type, an exploratory study in goal, a quantitative and qualitative study in data type, and a field study in procedure, in which questionnaire and interview were used as the research instrument. The statistical population was composed of the experts of the steel industry, out of whom 25 experts were selected as the statistical sample by the purposive technique. Data were analyzed by the fuzzy DEMATEL and fuzzy network process analysis in the SPSS21 and MS-Excel software packages. Then, the fuzzy Delphi technique was used, resulting in the identification of five criteria and 25 subcriteria. Then, the fuzzy DEMATEL was employed to determine the influence and dependence of the factors according to which among the main factors, the environment factor was the most influential with an influence value of 0.792 and the financial factor was the most dependent factor with a net dependence value of -0.996. Also, the identified factors were ranked by the fuzzy analytical network process. The results show that the financial factor has the highest weight. Also, the other factors are in the order of environmental, quality, environment, and technology in terms of importance.
This paper proposes a satisfying optimization method for fuzzy multiple objective optimization problem. Actually, the presented method realizes the trade-off between optimization and fuzzy importance requirement. Generally, the main aim of the presented approach is to make the more important objective achieving the higher desirable satisfying degree. In practice, vagueness and imprecision of the goals, constraints and parameters in this problem make the decision-making complicated for decision makers who have to deal with the parameters to make the optimized decision. Hence, the reformulated optimization models based on goal programming is proposed for different fuzzy relations and fuzzy importance. In fact, decision makers can select the appropriate alternative considering their determinations from variety of solutions using parameter λ. Applying the proposed model, not only the satisfying results of all the objectives can be acquired, but also the fuzzy importance requirement can be simultaneously actualized. In addition, a numerical example is provided to illustrate how the model is applied. Finally, the conclusions and recommendations are presented.
Data envelopment analysis (DEA) has been proven as an excellent data-oriented efficiency analysis method for comparing decision making units (DMUs) with multiple inputs and multiple outputs. In conventional DEA models, it is assumed that the input or output variables are all non-negative and desirable. However, in some situations, a performance measure can take positive quantity for some DMUs and negative value for others. Also, undesirable (bad) inputs and outputs may be presented in the production process. Hence, the standard model cannot directly reflect the efficiency score. The paper proposes a modified model in which both undesirable and negative data are treated to improve the relative efficiency of the DMU under evaluation. The focus of this paper is on treating the negative data on the definition of the two non-negative variable and the decreasing of undesirable outputs. A real example of 20 bank branches shows applicability of the proposed approach
Railway freight stations roles as points in which traffic processes can be merged and diverged are of paramount importance. Numerous activities such as train formation, alighting and interchanging, technical checks are also done at these points. Due to the great importance of using railway infrastructures and rolling stocks facilities efficiently, the efficiency studies in this area are considered as a demanding task more than ever. Therefore, we implement a methodology based on data envelopment analysis to address this issue. The suggested methodology in this research can be used for measuring the efficiency of railway freight stations and ranking them by using DEA and Anderson & Peterson methods. This methodology can be used for analyzing the relative ‘technical efficiency’ of railway freight stations to manage train stops regarding the current station capacity. We applied this model in a case study of the 12 busiest train stations in Isfahan railway to measure and rank their efficiency and assess the effect of traffic type on the results by using robust regression.
In this paper we apply an approximate method based on Galerkin approach with Legendre wavelets basis, on a class of fourth order boundary value problems. The approach reduces the main equation to a system of linear algebraic equations that could be solved numerically. The operational matrix of the method is obtained, and the convergence of the method is proved. we approximate the solution and its higher order derivatives, for some special examples and compare the results with some other numerical methods. The results show the effectiveness of the proposed method.
Due to improvement of Internet, employing web services is developed. By utilizing web services, distributed applications can exchange information. Trust is a main criterion to choose the proper web service as web services selection is a main issue which is still absorbing researchers to conduct research works on this field and analyze it. Due to the significant of this problem, neuro-fuzzy system is used to optimize the trust of single web services. Eight factors such as QoS, user preferences, subjective perspectives, objective perspectives, credibility of raters, bootstrapping, dynamic computing of trust and independency are considered in the considered neuro-fuzzy system. To achieve a trust optimization, 8 membership function various neuro-fuzzy systems are considered in this paper. Ultimately, the obtained results illustrates that the root mean square error, the precision amount, the recall amount and the F score amount of the neuro-fuzzy system is: 0.0873 %, 0.986, 0.988 and 0.987.
Land leveling is one of the most important steps in soil preparation for consequent objectives. Parallel policies need to take both energy and environmental subjects into the account as well as certain financial development and eco-friendly protection. Energy is one of the most important elements in agricultural sector. Nevertheless, pollution is linked with the usage of fossil fuels (particularly gasoline) as an energy source. Earthwork optimization plays an important role in reducing the total cost of highway projects. In this research, ICA has been followed to optimize earthwork volume for minimizing energy consumption of agricultural land leveling compared to minimum least squares, genetic algorithm, particle swarm optimization (PSO) have been employed for developing of optimization the energy related and other parameters. The study was specified based on the proposed land leveling project in district of Ahwaz, Iran. The study farm was a 70 ha area and located in the west of Iran. Topography of the farm was mapped in the scale of mapping as fine as 1:500. The outputs of the plan were length, width and height of points (coordinates of x, y and z) and the grid size in the region was 20 m×20 m. The aim of this work was use of new techniques and specifically optimization methods such as Imperialist competitive algorithm, genetic algorithms and PSO in modeling the leveling plane to minimize cut and fill volume and consequently the amount of energy consumption of leveling operations. It has been assumed that soil cut and fill volumes are equal and no need to move/ remove excessive soil. Therefore, there is no need to define a cut/fill variable in the model based on ICA. The results indicated that ICA offers a plan of earthwork, minimizing energy consumption of land leveling more efficiently than minimum least squares, genetic algorithm and PSO.
This paper suggests a new and efficient method for solving linear quadratic optimal control problems. A shifted chebyshev matrix approach is implemented for solving this problem. In this method, the problem of optimal control changes into a problem of non-linear programming which can be solved easily. The corresponding nonlinear programming problem will be solved using Matlab software to find the unknown coefficients which are related to the approximate solution. Numerical examples are also given in order to compare this new method with another one.
This paper present the existence and uniqueness of quadrupled fixed point theorems, whose method is quite primarily based definitely on Perov-type fixed point theorem for contraction in metric spaces equipped with vector-valued matrices. Furthermore, the study consist of Ulam-Hyers stability results for quadrupled fixed points of contractive type single valued mappings on complete metric spaces will be obtained.
Todays, industries are seeking the ways to improve their competitiveness and responsiveness in order to achieve the most share of markets and customer satisfaction. Optimization of strategic and tactical decisions in a logistics network would improve total performance of the supply chain in a long term planning horizon. This paper presents a Mixed-integer linear programming (MILP) model to optimize logistics networks under real limitations such as demand, capacity, and budget constraints. Due to NP-hard nature of the proposed model a Differential Evolutionary (DE) algorithm is proposed to solve the large sizes of the presented model in reasonable time. Finally, the computational results obtained through the DE algorithm are compared with the solutions obtained by GAMS optimization software. The results reveal that the proposed methodology is an efficient tool to optimize large scale logistics networks.
There exist large varieties of conjugate gradient algorithms. In order to take advantage of the attractive features of Liu and Storey (LS) and Conjugate Descent (CD) conjugate gradient methods, we suggest hybridization of these methods in which the parameter is computed as a convex combination of and respectively which the conjugate gradient (update) parameter was obtained from Secant equation. The algorithm generates descent direction and when the iterate jam, the direction satisfy sufficient descent condition. We report numerical results demonstrating the efficiency of our method. The hybrid computational scheme outperform or comparable with known conjugate gradient algorithms. We also show that our method converge globally using strong Wolfe condition.
Adomian decomposition method and He’s variational Iteration method are applied to nonlinear oscillator problems that involve conservative type of oscillators. The methods proved to be effective for the general and specific cases due to their algorithms that admit nonlinear terms in the problems. The two methods are tested on some specific problems in the literature, and the results obtained compared favourably with those obtained via the use of Energy balance method.
The COVID-19 pandemic has affected many people around the globe. Europe, as one of the most seriously affected continents, has been struggling with the novel coronavirus for several months. Obviously, outbreak response management plays a critical role in the impact of the disease. Therefore, in this paper, Malmquist Productivity Index is used to evaluate the performance of the most severely affected European countries based on the average contagion rate. The results rank the countries and provides insight for the future.
In this article, through symbolic computation With Maple, we get the solution of the (1 + 1)-dimensional Biharmonic-equation. These solutions, which we call lump solution, obtained using square functions, are rationally localized in all directions in the space. It should be noted that not all nonlinear partial differential equations have a lump solution. Finally, by selecting the appropriate parameter, the lump solutions are shown in the figures.
