Interval linear programming extends classical linear optimisation by allowing coefficients in the objective function and constraints to be specified as intervals rather than fixed values. This ...

Moving heavy materials through cutting, polishing and coating stages requires precise balancing of load capacity and motion speed. Here’s how the right linear guidance selection and configuration can ...

This project implements a CVaR-minimizing portfolio optimization model based on the seminal paper "Optimization of Conditional Value-at-Risk" by Rockafellar and Uryasev (2000). The analysis uses ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using pseudo-inverse training. Compared to other training techniques, such as stochastic gradient descent, ...

To fulfill the 2 Core Courses, take two Core Courses from two different Core Areas. CSE Core Courses are classified into six areas: Introduction to CSE, Computational Mathematics, High Performance ...

Abstract: Energy optimization is a critical challenge in wireless sensor networks (WSNs) due to its direct impact on the network lifetime. This paper proposes the use of the K-means algorithm combined ...

HiGHS is a high performance serial and parallel solver for large scale sparse linear optimization problems of the form $$ \min \quad \dfrac{1}{2}x^TQx + c^Tx \qquad \textrm{s.t.}~ \quad L \leq Ax \leq ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is the simplest machine learning technique to predict a single numeric value, ...

1 Department of Statistic, Federal University of Technology Owerri, Owerri, Nigeria. 2 Department of Entrepreneurship and Innovation Technology, Federal University of Technology Owerri, Owerri, ...

This paper deals with linear programming techniques and their application in optimizing lecture rooms in an institution. This linear programming formulated based on the available secondary data ...