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Research in mobile grid computing is inspired by the broad benefits of intensive scientific and enterprise applications by the scientific community in grid and mobile computing. The primary aim of grid computing is to combine the power of wide-ranging resources that are very diverse in nature and provide users with essential services to users in the future. Resources are complex and varying in a mobile grid system and the availability is limited for a period of time. With resource mobility in mind, classification is the most challenging and primitive challenge in the mobile grid environment. The previous paradigm outlined the Quantum based approach on Gravitational search Algorithm (QBGSA) for scheduling the task (job) on a mobile computing grid. In any case, it has problem with computational difficulty and execution time. To solve this problem, the proposed system designed an Intuitionistic Fuzzy C-Means (IFCM) clustering and Natural Exponential Inertia Weight with Artificial Bee Colony (NEIWABC) based scheduling approaches. In this proposed research work, grid server has all the information about mobile grid networks. Once it receiving the task request from user, it verifies the available resource providers. The nodes are clustered by using Intuitionistic Fuzzy C-Means (IFCM) clustering algorithm and Cluster Head (CH) selection is done using mobile capacity such as storage capacity, computational power. Then the task request is promoting to the selected CH in the cluster. Then the CH schedules the jobs to the appropriate mobiles to respond user. The task scheduling is performed by using Natural Exponential Inertia Weight with Artificial Bee Colony (NEIWABC) algorithm. The results of this experiment depicts that the proposed system attains good efficiency on comparison with previous system. [ABSTRACT FROM AUTHOR]

A new way of formalizing and solving various control problems for the important class of dynamic systems known as DES is suggested. The formalization is based on the original first-order logic calculus of the positively-constructed formulas (PCF). A PCF-based algorithm for checking the co-observability property of a specification language restricting DES behavior is presented. Co-observable languages serve as specifications for the decentralized supervisors, which are necessary to implement group control tasks. The approach is demonstrated on the example of a discrete-event model of an autonomous underwater vehicle, which describes AUV’s high-level operation modes switching while following the leader, in a surveillance mission, performed by the AUV group. [ABSTRACT FROM AUTHOR]

The problem of bringing control system in space Rn to a target set at a given time moment is considered in the paper. System's behavior is described by the system of di_erential equations on which standard conditions of existence, uniqueness and extendability of a solution of the system are implied for a given time period. The 2-stage method is proposed for finding approximate solution. Sets of solvability in a discrete model are constructed on the first stage. On the second stage procedure of constructing the solving control takes place. This procedure utilizes the points of constructed sets as guides. Program complex based on proposed method was implemented in order to provide numerical experiments using computers. The article contains the results of one of these experiments. [ABSTRACT FROM AUTHOR]

The paper deals with the development of algorithms for solving nonlinear problems of heat conduction in bodies consisting of layered metal composites. The nonlinearity of the problems is governed by the temperature dependence of the heat conductivity coefficients of the composite layer materials. Mathematical models and solution algorithms based on the boundary element method have been constructed for one-dimensional cases of heat distribution. [ABSTRACT FROM AUTHOR]

We present an application of distributed consensus algorithms to metamorphic systems. A metamorphic system is a set of identical units that can self-assemble to form a rigid structure. For instance, one can think of a robotic arm composed of multiple links connected by joints. The system can change its shape in order to adapt to different environments via reconfiguration of its constituting units. We assume in this work that several metamorphic systems form a network: two systems are connected whenever they are able to communicate with each other. The aim of this paper is to propose a distributed algorithm that synchronizes all the systems in the network. Synchronizing means that all the systems should end up having the same configuration. This aim is achieved in two steps: (i) we cast the problem as a consensus problem on a metric space and (ii) we use a recent distributed consensus algorithm that only make use of metrical notions. [ABSTRACT FROM AUTHOR]

This paper describes a simulation system according to improve steelmaking's efficiency and to monitor its performances by anticipating the next period workload. Usually the production planning in those cases is made by the use of Gantt diagrams, based on operator's work. This means that if an accident occurs, the operator himself has to change in few minutes the production plan with a lower performance than the original one. The first consideration is obviously that the operator's experience itself it's not sufficient to re-plan a performing steelmaking chain. Hence the necessity of simulation as problem-solving technique in this complex situation. A brief introduction on this paper is devoted to identify the common problems in most plants about production planning, and this is indeed needed to define the boundary conditions and the framework of the problem. Then, a description of steelmaking processes and the general features of critical aspects about steelmaking planning (Paragraph 2) is given in order to understand the bonds, features, criticalities to be analyzed and implemented in the simulation model. In paragraph 3 a detailed analysis of proposed methodology and system architecture is given in order to make the reader understand the complexity that the Authors had to face in modeling the system and the solutions they found with approximations, considerations, techniques and algorithms that were the most suitable to be used in this particular situation. A short description of the likely steelmaking plant modeled and Verification and Validation (V&V) results are carried in paragraph 4. It was in fact very important in such a complex system, to define the acceptability of results in terms of verification of the correctness, validation of the results, and accreditation to the users. This is a generally valid principle in simulation, but moreover in a complex system modeling such a steelmaking process, where an error can cost millions. At last, in paragraph 5, the Authors present the conclusions of this work, with a particular attention to the savings that the simulation can bring to this real system, explaining the results of the case study to which it was applied, and the possible future developments of this research are discussed. This model can anyway be applied to other realities than the one exemplified in this paper. [ABSTRACT FROM AUTHOR]

Fuzzy Topographic Topological Mapping (FTTM) is a model for solving neuromagnetic inverse problem. FTTM consists of four components and connected by three algorithms. FTTM version 1 and FTTM version 2 were designed to present 3D view of an unbounded single current and bounded multicurrent sources, respectively. In 2008, Suhana introduced some definitions on sequence ofFTTM. One ofthe features produced from the sequences ofFTTM is Cube of FTTM. A cube ofFTTM is a combination of two or more FTTM in FTTM«. In this paper, cube of finite vertices ofFTTM, namely FKn are discussed. Consequently, some theorems are proven in order to describe patterns for sequence of cubes for FKn based on this k-Fibonacci sequence. Interestingly, the cube oí FKn appears to be an example ofgeneralized Fibonacci sequence, namely the k-Fibonacci sequence. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a concept of a soft matrix on a soft multiset, and investigate how to use soft matrices to solve decision making problems. An algorithm for a multiple choose selection problem is also provided. Finally, we demonstrate an illustrative example to show the decision making steps. [ABSTRACT FROM AUTHOR]

The paper is dedicated to the 80th birthday and the memory and honoring of late Professor V. Matrosov. He was an outstanding scientist, who contributed much to development of the stability and control theories as well as to development of different applications. In particular, he developed in algorithmic form a comparison method with vector Lyapunov function as rather unified and efficient method of nonlinear analysis and applications in systems dynamics and control theory, and we consider here mostly these results. [ABSTRACT FROM AUTHOR]

Problems of swarm robotics are extensively studied in contemporary robotics. In this paper, we consider the problem of robot swarms control with only global signals. We propose an efficient approach to solve the problem. In particular, we consider an explicit reduction from the decision version of the problem to the satisfiability problem. For different satisfiability algorithms, we present the results of computational experiments. [ABSTRACT FROM AUTHOR]

In this paper a hybrid algorithm is proposed to find the optimal solution for any instance of the bin packing problem one-dimensional. The hybrid algorithm considers the use of a heuristic method and a mathematical model based on flow arcs technique to find the optimal solution for an instance of 1D-BPP. The hybrid algorithm makes use of the lower bound of an instance as an element that allows it to identify if it have found the optimum or starting from this value it must find the optimal solution. The experiments were performed using the instances of the hard28 set, finding it the optimal solutions for all instances. The results show that the developed algorithm, called AHR, used 75% less time than using the Valerio model. [ABSTRACT FROM AUTHOR]

The most common approach for solving constrained optimization problems is based on penalty functions, where the constrained problem is transformed into a sequence of unconstrained problem by penalizing the objective function when constraints are violated. In this paper, we analyze the implementation of an adaptive penalty method, within the DIRECT algorithm, in which the constraints that are more difficult to be satisfied will have relatively higher penalty values. In order to assess the applicability and performance of the proposed method, some benchmark problems from engineering design optimization are considered. [ABSTRACT FROM AUTHOR]

In open vehicle routing problems, the vehicles are not required to return to the depot after completing service. In this paper, we present the first exact optimization algorithm for the open version of the well-known capacitated vehicle routing problem (CVRP). The strategy of releasing nonbasic variables from their bounds, combined with the 'active constraint' method and the notion of superbasics, has been developed for efficiently requirements; this strategy is used to force the appropriate non-integer basic variables to move to their neighborhood integer points. A study of criteria for choosing a nonbasic variable to work with in the integerizing strategy has also been made. [ABSTRACT FROM AUTHOR]

Integer goal programming problems arise quite naturally in many real-world applications. In this paper, we propose a reference direction approach and interactive algorithm to solve integer goal programming problem. We use analytic hierarchy process (AHP) to get the reference direction. At each iteration, only one integer linear programming problem is solved to get an efficient solution. Through analytic hierarchy process the decision maker has to provide the preference point such that the original problem has been transformed into linear integer programming model. [ABSTRACT FROM AUTHOR]

In the course of solving problems of managing and planning the development of large transport networks, a big amount of heterogeneous data from various sources is accumulated. The methods of graph theory are used to systematize information, process it, and calculate network characteristics. However, the problem arises of the enormous complexity and duration of computations over graphs of large networks. One of the approaches to solve this problem is the simplification of the original graph. In our report we study the influence of processing and basic graph simplification on the initial properties of the network. [ABSTRACT FROM AUTHOR]

The traditional collaborative filtering algorithm only pays attention to the rating by users. In reality, however, user and item information is always changing with time flying. Therefore, recommendation systems need to take timevarying changes into consideration. The collaborative filtering algorithm which is based on Forgetting Curve and Long Tail theory (FCLT) is introduced for the above problems. The following two points are discussed depending on the problem: First, the user-item rating matrix can update in real time by forgetting curve; secondly, according to the Long Tail theory and item popularity, a further similarity calculation method is obtained. The experimental results demonstrated that the proposed algorithm can effectively improve the recommendation accuracy and alleviate the Long Tail effect. [ABSTRACT FROM AUTHOR]

Many routing problems arising in different applications can be interpreted as a discrete optimization problem with additional constraints. The latter include generalized travelling salesman problem (GTSP), to which task of tool routing for CNC thermal cutting machines is sometimes reduced. Technological requirements bound to thermal fields distribution during cutting process are of great importance when developing algorithms for this task solution. These requirements give rise to some specific constraints for GTSP. This paper provides a mathematical formulation for the problem of thermal fields calculating during metal sheet thermal cutting. Corresponding algorithm with its programmatic implementation is considered. The mathematical model allowing taking such constraints into account considering other routing problems is discussed either. [ABSTRACT FROM AUTHOR]

The multiplicative measure and estimation method of ordering of the nearest neighborhood at the multiscale "site" percolation problem are considered. In the report also is shown the possibility of quantifying a relative degree of order of two nearest neighborhoods, which is based on the algorithm proposed by one of the authors. Moreover, the model of the oscillatory component of interaction of inner boundaries of different scales is proposed. In the context of our report, the concept of lacunarity and effective dimension (introduced by B. Mandelbrot) is discussed as effective tools of mathematical modeling. [ABSTRACT FROM AUTHOR]

The digital piracy involving images, music, movies, books, and so on, is a legal problem that has not found a solution. Therefore it becomes crucial to create and to develop methods and numerical algorithms in order to solve the copyright problems. In this paper we focus the attention on a new approach of watermarking technique applied to digital color images. Our aim is to describe the realized watermarking algorithm based on multichannel wavelet functions with multiplicity r = 3, called MCWM 1.0. We report a large experimentation and some important numerical results in order to show the robustness of the proposed algorithm to geometrical attacks. [ABSTRACT FROM AUTHOR]

In a wide class of problems in insurance and financial mathematics, it is of interest to study the extremal events of a perpetuity sequence. This paper addresses the problem of numerically evaluating these rare event probabilities. Specifically, an importance sampling algorithm is described which is efficient in the sense that it exhibits bounded relative error, and which is optimal in an appropriate asymptotic sense. The main idea of the algorithm is to use a 'dual' change of measure, which is employed to an associated Markov chain over a randomly-stopped time interval. The algorithm also makes use of the so-called forward sequences generated to the given stochastic recursion, together with elements of Markov chain theory. [ABSTRACT FROM AUTHOR]

Machine breakdowns in a production schedule may occur on a random basis that make the well-known hard combinatorial problem of Job Shop Scheduling Problems (JSSP) becomes more complex. One of popular techniques used to solve the combinatorial problems is Tabu Search. In this technique, moves that will be not allowed to be revisited are retained in a tabu list in order to avoid in gaining solutions that have been obtained previously. In this paper, we propose an algorithm to employ a second tabu list to keep broken machines, in addition to the tabu list that keeps the moves. The period of how long the broken machines will be kept on the list is categorized using fuzzy membership function. Our technique are tested to the benchmark data of JSSP available on the OR library. From the experiment, we found that our algorithm is promising to help a decision maker to face the event of machine breakdowns. [ABSTRACT FROM AUTHOR]

This paper shows a complete approach to solve a given problem, from the experimentation to the optimization of different cutting parameters. In response to an industrial problem of slotting FSX 414, a Cobalt-based refractory material, we have implemented a design of experiment to determine the most influent parameters on the tool life, the surface roughness and the cutting forces. After theses trials, an optimization approach has been implemented to find the lowest manufacturing cost while respecting the roughness constraints and cutting force limitation constraints. The optimization approach is based on the Response Surface Method (RSM) using the Sequential Quadratic programming algorithm (SQP) for a constrained problem. To avoid a local optimum and to obtain an accurate solution at low cost, an efficient strategy, which allows improving the RSM accuracy in the vicinity of the global optimum, is presented. With these models and these trials, we could apply and compare our optimization methods in order to get the lowest cost for the best quality, i.e. a satisfying surface roughness and limited cutting forces. [ABSTRACT FROM AUTHOR]

This paper presents a gradient-related algorithm for solving large scale, spatially explicit, welfare models with transportation. It introduces the theory, describes the different components of the algorithm, and reports on experience gained in applying it. [ABSTRACT FROM AUTHOR]

In this paper we propose an exponential fitting (EF) method with two fitting parameters for solving initial value problem x" = f(x(t), x'(t)) which has oscillatory solutions with varying amplitude. Local truncation error formula is used to determine these fitting parameters. Numerical examples are presented to show efficiency of the method for oscillatory problems in the long time integration. [ABSTRACT FROM AUTHOR]

Thermal power plants (TPPs) can produce and supply electricity to power system as a main power source but power generation fuel cost of the TPPs is very expensive. So, the target of minimizing the cost is considered as a main duty in power system operation. This is called economic load dispatch (ELD) problem. In this paper, a novel algorithm, tunicate swarm algorithm (TSA), is applied for solving the ELD problem. The applied TSA is implemented for test systems with different numbers of units and different constraints such as power balance constraints, prohibited operating zones, power losses and power output limits of generators. The first test system is comprised of 6 units considering power balance constraints, power output limits, prohibited working zones and power losses while the second test system consists of 20 units taking into account the power balance constraints, power output limits and power losses. TSA is compared to a high number of previous methods in terms of the cost and TSA is concluded to be a powerful method since it can find less or equal cost with other compared methods. [ABSTRACT FROM AUTHOR]

In this work we consider a multiphase interface advection problem, solved with a volume of fluid (VOF) technique, coupled with a FSI problem. A Cartesian mesh grid and an unstructured one are used to solve the VOF and FSI problem, respectively. We propose a new algorithm to project the velocity field, solution of the FSI problem, into the Cartesian grid. The FSI and the energy balance problems are solved with a parallel multigrid C++ Finite Element code. [ABSTRACT FROM AUTHOR]

Listing of all n! distinct permutations is an exhaustive process. Using starter set, the process of listing the permutations becomes easy. However a problem arises when the equivalence starter sets will generate the similar permutation and needed to be discarded. Two new recursive strategies are proposed to generate starter sets without generating equivalence starter sets namely circular and exchange two elements operation. Once the starter sets are obtained, the circular and reverse of circular operation are employed to produce distinct permutation from each starter sets. Computational advantages are presented comparing the results obtained by the new method with two other existing methods. The result indicates that the exchange two elements based strategy is faster than the circular based. Overall all new algorithms are better than existing algorithms in time execution. [ABSTRACT FROM AUTHOR]

Genetic Algorithm (GA) is a search method that simulates the process of natural selection and it attempts to find a good solution to some problem by randomly generating a collection of potential solutions to the problem and then manipulating those solutions using genetic operators. Through selection, mutation and re-combination (crossover) operations, better solutions are hopefully generated out of the current set of potential solutions. This process continues until an acceptable solution is found. GA is becoming popular to solve the optimization problems mainly because of its robustness in finding optimal solution and ability to provide near optimal solution close to global optimum. The ELD approach is tested on sample 3-generator system with the load of 24 hours. [ABSTRACT FROM AUTHOR]

In the Bayesian mixture modeling requires stages the identification number of the most appropriate mixture components thus obtained mixture models fit the data through data driven concept. Reversible Jump Markov Chain Monte Carlo (RJMCMC) is a combination of the reversible jump (RJ) concept and the Markov Chain Monte Carlo (MCMC) concept used by some researchers to solve the problem of identifying the number of mixture components which are not known with certainty number. In its application, RJMCMC using the concept of the birth/death and the split-merge with six types of movement, that are w updating, θ updating, z updating, hyperparameter β updating, split-merge for components and birth/death from blank components. The development of the RJMCMC algorithm needs to be done according to the observed case. The purpose of this study is to know the performance of RJMCMC algorithm development in identifying the number of mixture components which are not known with certainty number in the Bayesian mixture modeling for microarray data in Indonesia. The results of this study represent that the concept RJMCMC algorithm development able to properly identify the number of mixture components in the Bayesian normal mixture model wherein the component mixture in the case of microarray data in Indonesia is not known for certain number. [ABSTRACT FROM AUTHOR]

In order to solve the problems of modification algorithm of NURBS curve interpolation, Such as interpolation time bigger, NURBS curve step error and chord error are not easy changed, and so on. A novel proposed a modification algorithm of NURBS curve interpolation. The algorithm has merits such as higher interpolation position accuracy, short processing time and so on. In this simulation, an open five-axis CNC platform based on SIEMENS 840D CNC system is developed for verifying the proposed modification algorithm of NURBS curve interpolation experimentally. The simulation results show that the algorithm is correct; it is consistent with a NURBS curve interpolation requirements. [ABSTRACT FROM AUTHOR]

In this work, we present a numerical study of a finite volume scheme based on SIMPLE algorithm for incompressible Navier-Stokes problem. However, this algorithm still not applicable to a large category of problems this could be understood from its stability and convergence, which depends strongly on the parameter of relaxation, in some cases this algorithm could have an unexpected behavior. Therefore, in our work we focus on this particular point to overcome this respected choice of relaxation parameter and to find a sufficient condition for the convergence of the algorithm in general cases. This will be followed by numerical applications in image processing variety of fluid flow problems described by incompressible Navier-Stokes equations. [ABSTRACT FROM AUTHOR]

Univariate box-constrained Lipschitz global optimization problems are considered in this contribution. Geometric and information statistical approaches are presented. The novel powerful local tuning and local improvement techniques are described in the contribution as well as the traditional ways to estimate the Lipschitz constant. The advantages of the presented local tuning and local improvement techniques are demonstrated using the operational characteristics approach for comparing deterministic global optimization algorithms on the class of 100 widely used test functions. [ABSTRACT FROM AUTHOR]

A two point block backward difference method is established to solve Riccati differential equations directly. Based on a predictor-corrector two point block backward difference method (2PBBD), a code is developed using a set of integration coefficients that eliminates the need to be calculated at every step change. The method requires calculating the integration coefficients only once in the beginning. The 2PBBD has an added advantage of a recurrence relationship between coefficients of different orders which provides a more elegant algorithm. The recurrence relationship between coefficients also reduces the computational cost. [ABSTRACT FROM AUTHOR]

This article discusses the possibilities in the area of modeling of the so called cooling tower plume emergent at operating evaporating cooling systems. As opposed to recent publication, this text focuses on the possibilities of a simplified analytic description of the whole problem where this description shall - in the future - form the base of a calculation algorithms enabling to simulate the efficiency of systems reducing this cooling tower plume. The procedure is based on the application of basic formula for the calculation of the velocity and concentration fields in the area above the cooling tower. These calculation is then used to determine the form and the total volume of the plume. Although this approach does not offer more exact results, it can provide a basic understanding of the impact of individual quantities relating to this problem. [ABSTRACT FROM AUTHOR]

We consider a model problem for the research of Earth's surface state caused by discharge of tectonic stress on the deep cracks in the earth's crust. Using the numerical method of bicharacteristics, algorithm is developed and solution of the problem of non-stationary dynamics of a homogeneous isotropic elastic half-space is built under plane strain when one resets the vertical stress on crack. Diffraction of waves on the surface is studied, pictures of wave fields and stress-strain state of the medium and the surface for different moments of time are built. [ABSTRACT FROM AUTHOR]

The simultaneous diagonalization problem of various size matrices is considered. We propose an algorithm for the problem that always finds a solution if one exists. The algorithm uses an algorithm for the simultaneous diagonalization of square matrices as a subroutine. [ABSTRACT FROM AUTHOR]

Based on the theory of radical constructivism, this study investigated Year Four pupils' understandings of division by identifying their schemes of the division of whole numbers and how they used them in solving related problematic situations. Data incorporating both verbal and non-verbal behaviors were gathered from seven pupils based on the five clinical interview sessions involving imagining division, representing division, describing process and product of division, interpreting division statement, and solving division problem tasks. Four schemes that were identified are partitioning scheme, measuring scheme, repeated subtraction scheme, and inverse of multiplication scheme. Findings revealed that the measuring scheme was the dominant scheme for the division of whole numbers and the pupils only used the repeated and the inverse of multiplication schemes when they were asked to relate the subtraction or multiplication process with the division process. Further, the pupils were observed to use the long division algorithm in some situations, but there were indications that they used them with little understandings. It is suggested that more remains to be learnt about the nature of pupils' understanding of the division of whole numbers and how schemes of the division of whole numbers are formed and modified. Also, in order to provide appropriate guidance, mathematics teachers need to have some knowledge about pupils' available schemes of the division of whole numbers, no matter how primitive they might seem to the teachers. [ABSTRACT FROM AUTHOR]

The Broyden family update in quasi-Newton method is known as one of the most efficient update method in solving unconstrained optimization. However, by using the standard search direction, sometimes the algorithm may lead to the failure for some complicated problems and this scenario worsen when the cases of the initial points selected are far away from the minimizer. To overcome this scenario, we proposed a new search direction by using the Fletcher Reeves formula in the conjugate gradient method to be fit with the new search direction. We proved that this new search direction globally converge and positively affect the Broyden family update in quasi-Newton method. [ABSTRACT FROM AUTHOR]

We developed a new approach for solving eigenvalue problem for the oligomer chain systems based on localized molecular orbitals (LMO) of the separated fragments within elongation method. The method performed in this work and implemented in elongation scheme yields excellent agreement with the conventional results. It has been demonstrated that the proposed algorithm for computing orbital energies and eigenvectors in elongation method reduces the CPU time usage up to 50%. [ABSTRACT FROM AUTHOR]

In this work we consider stationary periodic solutions of fourth-order semi-linear parabolic equation, arising in population dynamics and spatial patterns formation. First, using variational method, we establish existence of infinitely many solutions. Next we develop a fast numerical algorithm for solving the model problem. Numerical results are proposed and discussed. [ABSTRACT FROM AUTHOR]

We study a multicriteria location problem where several other criteria (for instance cost functions) are added to the locational criteria, then we investigate the reducibility of it and introduce a decomposition algorithm for solving such extended multicriteria location problems. Furthermore, we derive a corresponding computer program in MATLAB. [ABSTRACT FROM AUTHOR]

Here we present a primal-dual interior point method that relies on a filter line search method to promote global convergence of nonlinear optimization problems. Each entry in the filter includes two components directly taken from the first-order optimality conditions of the problem. Primal feasibility, complementarity and dual feasibility measures are used to compose the components. The logarithmic barrier function is also used to promote convergence to minimizers. The algorithm is tested with a benchmark set of nonlinear problems. [ABSTRACT FROM AUTHOR]

Here, we present some numerical experiments with a reduction method for solving nonlinear semi-infinite programming (SIP) problems. The method relies on a line search technique to ensure a sufficient decrease of a L2-exponential merit function. The proposed merit function is continuous for SIP and improves the algorithm efficiency when compared with other previously tested merit functions. A comparison with other reduction methods is also included. [ABSTRACT FROM AUTHOR]