Math. Comput. Appl., Volume 21, Issue 3 (September 2016) – 13 articles

To gain more competitive advantages and attract more customers from the turbulent business environment, manufacturing firms today must offer a wide variety of products to marketplaces. The existence of component commonality in multi-product fabrication planning enables managers to reevaluate different production design alternatives to lower overall production relevant costs. Motivated by assisting managers of manufacturing firms in gaining competitive advantages, maximizing machine utilization, and reducing overall quality and fabrication-distribution costs, this study explores a multi-product fabrication-distribution problem with component commonality, postponement, and quality assurance. A two-stage single-machine production scheme with the reworking of repairable nonconforming items is proposed. The first stage fabricates common intermediate components for all products, and the second stage produces and distributes end products under a common cycle time policy. Mathematical modeling and optimization techniques are utilized to derive the optimal fabrication-distribution policy that minimizes the expected total system costs of the problem. Finally, we provide a numerical example with sensitivity analyses to not only show practical uses of the obtained results, but also demonstrate that the proposed production scheme is beneficial in terms of cost savings and cycle time reduction as compared to that in a single-stage production scheme. The research results enable manufacturers to gain more competitive advantages in the turbulent global business environment. Full article

A particle filter is a powerful tool for object tracking based on sequential Monte Carlo methods under a Bayesian estimation framework. A major challenge for a particle filter in object tracking is how to allocate particles to a high-probability density area. A particle filter does not take into account the historical prior information on the generation of the proposal distribution and, thus, it cannot approximate posterior density well. Therefore, a new fuzzy grey prediction-based particle filter (called FuzzyGP-PF) for object tracking is proposed in this paper. First, a new prediction model which was based on fuzzy mathematics theory and grey system theory was established, coined the Fuzzy-Grey-Prediction (FGP) model. Then, the history state sequence is utilized as prior information to predict and sample a part of particles for generating the proposal distribution in the particle filter. Simulations are conducted in the context of two typical maneuvering motion scenarios and the results indicate that the proposed FuzzyGP-PF algorithm can exhibit better overall performance in object tracking. Full article

Our goal in this work is to introduce the notion $\left[V,,,\lambda \right]{\left(\mathcal{I}\right)}_2$ -summability and ideal λ-double statistical convergence of order α with respect to the intuitionistic fuzzy norm $\left(\mu ,,,v\right)$ . We also make some observations about these spaces and prove some inclusion relations. Full article

By extending the definition interval of the standard cubic Catmull-Rom spline basis functions from [0,1] to [0,α], a class of cubic Catmull-Rom spline basis functions with a shape parameter α, named cubic α-Catmull-Rom spline basis functions, is constructed. Then, the corresponding cubic α-Catmull-Rom spline curves are generated based on the introduced basis functions. The cubic α-Catmull-Rom spline curves not only have the same properties as the standard cubic Catmull-Rom spline curves, but also can be adjusted by altering the value of the shape parameter α even if the control points are fixed. Furthermore, the cubic α-Catmull-Rom spline interpolation function is discussed, and a method for determining the optimal interpolation function is presented. Full article

Clustering analysis based on a mixture of multivariate normal distributions is commonly used in the clustering of multidimensional data sets. Model selection is one of the most important problems in mixture cluster analysis based on the mixture of multivariate normal distributions. Model selection involves the determination of the number of components (clusters) and the selection of an appropriate covariance structure in the mixture cluster analysis. In this study, the efficiency of information criteria that are commonly used in model selection is examined. The effectiveness of information criteria has been determined according to the success in the selection of the number of components and in the selection of an appropriate covariance matrix. Full article

The auxiliary problem principle has been widely applied in power systems to solve the multi-area economic dispatch problem. Although the effectiveness and correctness of the auxiliary problem principle method have been demonstrated in relevant literatures, the aspect connected with accurate estimate of its convergence rate has not yet been established. In this paper, we prove the $O(1/n)$ convergence rate of the auxiliary problem principle method. Full article

In this paper, with the help of the Hardy and Dedekind sums we will give many properties of the sum $B_1(h,k)$ , which was defined by Cetin et al. Then we will give the connections of this sum with the other well-known finite sums such as the Dedekind sums, the Hardy sums, the Simsek sums $Y(h,k)$ and the sum $C_1(h,k)$ . By using the Fibonacci numbers and two-term polynomial relation, we will also give a new property of the sum $B_1(h,k)$ . Full article

The purpose of this work is to introduce a new kind of finite difference formulation inspired from Fourier analysis, for reaction-diffusion equations. Compared to classical schemes, the proposed scheme is much more accurate and has interesting stability properties. Convergence properties and stability of the scheme are discussed. Numerical examples are provided to show better performance of the method, compared with other existing methods in the literature. Full article

Image mosaicing sits at the core of many optical mapping applications with mobile robotic platforms. As these platforms have been evolving rapidly and increasing their capabilities, the amount of data they are able to collect is increasing drastically. For this reason, the necessity for efficient methods to handle and process such big data has been rising from different scientific fields, where the optical data provides valuable information. One of the challenging steps of image mosaicing is finding the best image-to-map (or mosaic) motion (represented as a planar transformation) for each image while considering the constraints imposed by inter-image motions. This problem is referred to as Global Alignment (GA) or Global Registration, which usually requires a non-linear minimization. In this paper, following the aforementioned motivations, we propose a two-step global alignment method to obtain globally coherent mosaics with less computational cost and time. It firstly tries to estimate the scale and rotation parameters and then the translation parameters. Although it requires a non-linear minimization, Jacobians are simple to compute and do not contain the positions of correspondences. This allows for saving computational cost and time. It can be also used as a fast way to obtain an initial estimate for further usage in the Symmetric Transfer Error Minimization (STEMin) approach. We presented experimental and comparative results on different datasets obtained by robotic platforms for mapping purposes. Full article

The problem of quantifying the vulnerability of graphs has received much attention nowadays, especially in the field of computer or communication networks. In a communication network, the vulnerability measures the resistance of the network to disruption of operation after the failure of certain stations or communication links. If we think of a graph as modeling a network, the average lower 2-domination number of a graph is a measure of the graph vulnerability and it is defined by ${\mathsf{\gamma }}_{2av}(G)=\frac{1}{\left|V(G)\right|}{\sum }_{v\in V(G)}{\mathsf{\gamma }}_{2v}(G)$ , where the lower 2-domination number, denoted by ${\mathsf{\gamma }}_{2v}(G)$ , of the graph G relative to v is the minimum cardinality of 2-domination set in G that contains the vertex v. In this paper, the average lower 2-domination number of wheels and some related networks namely gear graph, friendship graph, helm graph and sun flower graph are calculated. Then, we offer an algorithm for computing the 2-domination number and the average lower 2-domination number of any graph G. Full article

Evaluation on achievement of scientists plays an important role in efficiently mining information of human resources. A metrics model, which is employed to calculate the number of academic papers, research awards and scientific research projects, often significantly affects the degree of fairness as it is used to compare the achievements of more than one scientist. In particular, it often becomes difficult to quantify the achievement for each scientist if there are a lot of participants in the same research output. In this paper, a new nonlinear metrics model, called a credit function, is established to mine the information of the individual research outputs (IRO). An example is constructed to show that different credit functions may generate distinct ranking for the scientists. By the proposed nonlinear methods in this paper, the inequality relation of contribution in the same IRO can be quantified, and the obtained ranking on the scientists is more acceptable than the existing linear method available in the literature. Finally, the proposed metrics model is applied in solving three practical problems, especially combined with the technique for order preference by similarity to an ideal solution (TOPSIS). Full article

In the paper, the authors derive an integral representation, present a double inequality, supply an asymptotic formula, find an inequality, and verify complete monotonicity of a function involving the gamma function and originating from geometric probability for pairs of hyperplanes intersecting with a convex body. Full article