This paper investigates the asymptotic and nonasymptotic behavior of the quantized primal-dual (PD) algorithm in network utility maximization (NUM) problems, in which a group of agents maximizes the ...

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 ...

The PDLP (Primal-Dual Hybrid Gradient enhanced for Linear Programming) solver improves the performance and reliability of PDHG by implementing a restarted version of the algorithm. The standard PDHG ...

I want to add a transmission section constraint by limiting the sum of the transmission power of a few transmission lines of the branch matrix, and then apply this simple linear constraint using ...

In this article, we propose new constraints that can be used for tightening such convex relaxation. These constraints are derived from the physical information lost due to relaxation and require ...

Meanwhile, the trajectory generation is formulated as a convex optimization problem with a nonlinear objective function and constraints. Then, the problem is solved with a typical linear programming ...

After reducing the dimension of the linear programming problem using the subset of the essential constraints, the solution method can be chosen from any suitable method for linear programming. The ...

Learn about the challenges and limitations of linear and nonlinear programming in practice, and how to overcome them with suitable models, methods, and tools.

This article adopts multi-objective linear programming (MOP) as the optimization model of land use structure. The principle of the model is to set the objective function and constraints conditions, ...