This paper proposes an improved predictor-corrector interior-point algorithm for the linear complementarity problem LCP based on the Mizuno-Todd-Ye algorithm. The modified corrector steps in our algorithm cannot only draw the iteration point back to a narrower neighborhood of the center path but also reduce the duality gap. It implies that the improved algorithm can converge faster than the MTY...

The objective of this study is to identify a model able to represent the behavior of the historical decision maker (DM) in the management of lake Lugano, during the period 1982–2002. The DM decides every day how much water to release from the lake. We combine hydrological knowledge and machine learning techniques to properly develop the model. As a predictive tool we use lazy learning, namely l...

There has been a great deal of success in the last twenty years with the use of cutting plane algorithms to solve specialized integer programming problems. Generally, these algorithms work by solving a sequence of linear programming relaxations of the integer programming problem, and they use the simplex algorithm to solve the relaxations. In this paper, we describe experiments using a predicto...

The main goals of this paper are to: i) relate two iteration-complexity bounds derived for the Mizuno-Todd-Ye predictor-corrector (MTY P-C) algorithm for linear programming (LP), and; ii) study the geometrical structure of the LP central path. The first iteration-complexity bound for the MTY P-C algorithm considered in this paper is expressed in terms of the integral of a certain curvature func...

The Mizuno–Todd–Ye predictor–corrector method based on two neighborhoods DðaÞ DðaÞ of the central path of a monotone homogeneous linear complementarity problem is analyzed, where DðaÞ is composed of all feasible points with d-proximity to the central path less than or equal to a. The largest allowable value for a is 1.76. For a specific choice of a and a a lower bound of vn= ffiffiffi n p is ob...

page 1 Predictor Corrector Methods Predictor Corrector Methods form the basis of the most successful codes (Variable Step Variable Order Methods) for the solution of initial value problems of ordinary differential equations. Briefly, these methods have been successful because they occur in naturally arising families covering a range of orders, they have reasonable stability properties, and they...

Regression analysis is a widely used statistical technique to build model from set of data on two or more variables. Linear regression based linear correlation, and assumes that change in one variable accompanied by proportional another variable. Simple regression, bivariate for predicting the value (predictor); however, multiple which enables us analyse than predictor variable, commonly used. ...

inear prediction modelling is used in a diverse area of applications, such as data forecasting, speech coding, video coding, speech recognition, model-based spectral analysis, model-based interpolation, signal restoration, and impulse/step event detection. In the statistical literature, linear prediction models are often referred to as autoregressive (AR) processes. In this chapter, we introduc...

with Communication Delays ASHU AHUJA, S. K. AGGARWAL 2 Electrical Engineering Department, Maharishi Markandeshwar University, Mullana, INDIA [email protected], [email protected] Abstract:The presence of communication delay in modern load frequency control (LFC) systems complicates the design and implementation of the controller to achieve robust performance of the system. In th...