Convex piecewise linear programming is a small and useful extension to linear programming. Two Python modules will allow easy formulation of a PLP problem with variables and equations. The CBC solver ...

The fast-online linear programming algorithm uses the fast dual iterative algorithm and applies a “boosting” strategy by running K rounds of random permutation. This algorithm can approximate the ...

Optimization and linear programming can be used to model and solve various types of problems, such as linear, nonlinear, discrete, continuous, convex, or non-convex. Add your perspective ...

This paper presents a new heuristic to linearise the convex quadratic programming problem. The usual Karush-Kuhn-Tucker conditions are used but in this case a linear objective function is also ...

Abstract: Convexity is a key property to global optimal for mathematical programming. Previous convex fitting works can only guarantee convexity at table entries or sampled points using semi-definite ...

Common linear-phase approaches lead to convex optimization and efficient global solutions, but can be inefficient when the phase of the blocking filter is unimportant. Although direct ...

Course Description: Linear Programs (LPs) and Semidefinite Programs (SDPs) are central tools in the design and analysis of algorithms. In this course, we will study the mathematical foundations behind ...

An efficient algorithm is proposed for the solution of multiparametric convex nonlinear problems (NLPs). Based on an outer-approximation algorithm, the proposed iterative procedure involves the ...

Discover a new heuristic for linearizing convex quadratic programming problems. Explore the use of Karush-Kuhn-Tucker conditions and a linear objective function. Overcome unboundedness challenges with ...