computational methodscutting-plane methodsquadratic programming problemsSummary This chapter contains sections titled: Gradientlike Computational Methods for Nonlinear Programs Duality in Nonlinear Programming Additional Computational Methods for Nonlinear Programs Quadratic Programming Summary...
An Interior-Point Algorithm for Nonconvex Nonlinear Programming The paper describes an interior-point algorithm for nonconvex nonlinear programming which is a direct extension of interior-point methods for linear and qu... RJ Vanderbei,DF Shanno - 《Computational Optimization & Applications》...
Part II is concerned with finding convex formulations of the power flow equations using semidefinite programming (SDP). The potential of SDP relaxation for problems in power systems has been manifested in [Lavaei and Low, 2012], with further studies conducted in [Lavaei, 2011; Sojoudi and Lavaei...
pythonoptimizationlinear-programmingmodeling-languagenonlinear-programmingmathematical-programming UpdatedDec 18, 2024 Python casadi/casadi Star1.8k CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs....
These works are complementary in that they deal primarily with convex, possibly nondifferentiable, optimization problems and rely on convex analysis. By contrast the nonlinear programming book focuses primarily on analytical and computational methods for possibly nonconvex differentiable problems. It relies ...
This chapter deals with nonlinear programming problems when the objective function includes several variables and any type of constraints. There are several techniques to deal with such type of problems but here we are concerned with the Lagrange multiplier method applicable to nonlinear problems with ...
Nonlinear Programming contains the proceedings of a Symposium on Nonlinear Programming held in Madison, Wisconsin on May 4-6, 1970. This book emphasizes algorithms and related theories that lead to efficient computational methods for solving nonlinear programming problems. This compilation consists of 17...
Theoretical or Mathematical/ computational complexityconvergencedynamic programmingGaussian processesiterative methodslinear quadratic Gaussian controlnonlinear control systemsperformance indexproduction controlstochastic programmingStochastic optimal control problems are considered that are non-linear in the state dynamics,...
finite-dim simpler space), gradient descent method, ascent method (applying Ritz to inner layer of min-max formulation), penalty method, regularization (perturbation analysis gives an approximation of the solution to the regularized problem), duality method, dynamic optimization (dynamic programming?),...
On accelerating PL continuation algorithms by predictor—corrector methods Traditionally a simplicial algorithm is based on a fixed triangulation T of R n+1 and a corresponding piecewise linear approximation F T :R n+1 →R ... D Saupe - 《Mathematical Programming》 被引量: 8发表: 1982年 A ...