Integer and Nonlinear ProgrammingConvergence theory in nonlinear programming; Nonlinear programming, computational methods; Some practical methods of optimziation; Advanced algorithmic feature for general mathematical programming systems; Rank one methods for unconstrained optimization; A class of method for nonlinear programming with termination and convergence properties; Minimization of a convex function by relaxation; Application of the GRC algorithm to optimical control problems; Computational methods for least squares; Linear least squares and quadratic programming; Ritter's cutting plane method for nonconvex quadratic programming; Applications of nonlinear optimization to approximation problems; Nonlinear duality and qualitative properties of optimal growth; Stochastic programming; Nonlinear programming for models with joint chance constraints; Properties of a class of integer polyhedra; Faces of the gomory polyhedron. |
Contents
Preface | 1 |
necessary are ready to transform what has been mainly research into routine | 2 |
J A Tomlin Branch and bound methods for integer and non | 21 |
Copyright | |
23 other sections not shown
Common terms and phrases
Abadie algorithm applied approximation assume b₁ basic variables basis calculated coefficients column computational concave constraint set convergence convex convex function cutting plane Dantzig Davidon defined denote determined dual eigenvalues elements equality constraints equations evaluations face feasible directions feasible solution Fletcher given Gomory gradient method Hence hyperplanes inequality integer polyhedron integer programming interpolation inverse matrix iteration Kuhn-Tucker least squares linear constraints linear least squares linear programming problem linearly constrained local minimum lower bound Math mathematical programming matrix maximization minimization minimum multipliers non-negative nonlinear constraints nonlinear programming objective function obtained optimal solution optimum orthogonal P₁ parameters penalty function pivot positive definite procedure quadratic function quadratic programming satisfying second derivative Section sequence simplex method solving steplength subset tableau Theorem transformation unconstrained upper bound vector vertex Wolfe y₁ zero