By reformulating the linear multiplicative programming problem (LMP) as an equivalent nonconvex programming problem (EP), we present a new accelerating outcome space branch-and-bound algorithm for ...

Linear programming is one of the most widely applied solutions to optimization problems. This paper presents a privacy-preserving solution to linear programming for two parties when the cost, or ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the linear support vector regression (linear SVR) technique, where the goal is to predict a single numeric ...

Standard computer implementations of Dantzig's simplex method for linear programming are based upon forming the inverse of the basic matrix and updating the inverse after every step of the method.

We developed spreadsheet linear-programming models for planning shipments of finished goods between vendors, manufacturing plants, warehouses, and customers to minimize overall cost subject to maximum ...

About this issue Abstract In this paper, a novel modified optimization algorithm is presented, which combines Nelder-Mead (NM) method with a gradient-based approach. The well-known Nelder Mead ...

Both problems are very well known NP-hard problems and can be formulated as integer linear programming problems. Heuristic methods e.g. the " first fit decreasing " (FFD) and " greedy " algorithm (GA) ...

CSCI 5654: Linear Programming CSCI 5654: Linear Programming Instructor Fall 2016: Sriram Sankaranarayanan Prerequisites Calculus I,II + Algorithms + Linear Algebra. Topics Covered Roughly, we will ...