In this article, we propose and analyze a computational method for numerical solution of general two point boundary value problems. Method is tested on problems to ensure the computational eciency. We have compared numerical results with results obtained by other method in literature. We conclude that propose method is computationally ecient and eective.

This paper examines the question of modifying the decomposition of a partially separable function in order to improve computational eciency of large-scale minimization algorithms using a conjugate-gradient inner iteration. The context and motivation are given and the application of a simple strategy discussed on examples extracted from the CUTE test problem collection.

In this paper, we study the Generalized Bin Covering problem. For this problem an exact algorithm is introduced which can nd optimal solution for small scale instances. To nd a solution near optimal for large scale instances, a heuristic algorithm has been proposed. By computational experiments, the eciency of the heuristic algorithm is assessed.

This paper present a novel numerical algorithm for the linear one-dimensional heat and wave equation. In this method, a nite dierenceapproach had been used to discrete the time derivative while cubic spline isapplied as an interpolation function in the space dimension. We discuss theaccuracy of the method by expanding the equation based on Taylor series andminimize the error. The proposed metho...

The present paper deals with the learnability of indexed families L of uniformly recursive languages from positive data. We consider the in uence of three monotonicity demands and their dual counterparts to the e ciency of the learning process. The e ciency of learning is measured in dependence on the number of mind changes a learning algorithm is allowed to perform. The three notions of (dual)...

Data Envelopment Analysis (DEA) is an eciency measurement tool for evaluation of similar Decision Making Units (DMUs). In DEA, weights are assigned to inputs and outputs and the absolute eciency score is obtained by the ratio of weighted sum of outputs to weighted sum of inputs. In traditional DEA models, this measure is also equivalent with relative eciency score which evaluates DMUs in compar...

Super eciency data envelopment analysis(DEA) model can be used in ranking the performanceof ecient decision making units(DMUs). In DEA, non-extreme ecient unitshave a super eciency score one and the existing super eciency DEA models do notprovide a complete ranking about these units. In this paper, we will propose a methodfor ranking the performance of the extreme and non-extreme ecient units.

One of the issues in Data Envelopment Analysis (DEA) is sensitivity and stability region of the speci c decision making unit (DMU), included ecient and inecient DMUs. In sensitivity analysis of ecient DMUs,the largest region should be found namely stability region thatdata variations are only for ecient DMU under evaluation and the data for the remainingDMUs are assumed xed. Also ecient DMU u...

Traditional DEA models deal with measurements of relative eciency ofDMUs regarding multiple - inputs VS. multiple-outputs. One of the drawbacksof these model is the neglect of intermediate products or linkong activities. Af-ter pointing out needs for inclusion of them to DEA models. We propose hybridmodel that can deal with intermediate products formally using this model wecan evaluate division...