Add to ORKGNew iterative separable programming techniques based on two-segment, piecewise-linear approximations are described for the minimization of convex separable functions over convex sets. These techniques have two advantages over traditional separable programming methods. The first is that they do not require the cumbersome "fine grid" approximations employed to achieve high accuracy in the usual separable programming approach. In addition, the new methods yield feasible solutions with objective values guaranteed to be within any specified tolerance of optimality. In computational tests with real-world problems of up to 500 "nonlinear" variables the approach has exhibited rapid convergence and yielded very close bounds on the optimal...
The assumed global optimum solution obtained in linear programming is not an assumed characteristic ...
We consider N-fold 4-block decomposable integer programs, which simultaneously generalize N...
AbstractThe problem of minimizing a separable nonlinear objective function under linear constraints ...
In this book, the author considers separable programming and, in particular, one of its important ca...
We present a constructive approach to solving convex programming problems in separable form and new...
AbstractComputable lower and upper bounds on the optimal and dual optimal solutions of a nonlinear, ...
We consider the convex minimization problem with linear constraints and a block-separable objective ...
The paper considers the minimization of a separable convex function subject to linear ascending cons...
AbstractWe define a new measure of the structure of a linear constraint matrix and establish some pr...
Consider the minimization problem with a convex separable objective function over a feasible region ...
The methods discussed are based on local piecewise-linear secant approximations to continuous conve...
We consider the linearly constrained separable convex programming, whose objective function is separ...
The equivalent formulation of a convex optimization problem is the computation of a value of a conju...
Convex programming has played an important role in studying a wide class of applications arising fro...
We discuss two models from the literature that have been developed to formulate piecewise linear app...
The assumed global optimum solution obtained in linear programming is not an assumed characteristic ...
We consider N-fold 4-block decomposable integer programs, which simultaneously generalize N...
AbstractThe problem of minimizing a separable nonlinear objective function under linear constraints ...
In this book, the author considers separable programming and, in particular, one of its important ca...
We present a constructive approach to solving convex programming problems in separable form and new...
AbstractComputable lower and upper bounds on the optimal and dual optimal solutions of a nonlinear, ...
We consider the convex minimization problem with linear constraints and a block-separable objective ...
The paper considers the minimization of a separable convex function subject to linear ascending cons...
AbstractWe define a new measure of the structure of a linear constraint matrix and establish some pr...
Consider the minimization problem with a convex separable objective function over a feasible region ...
The methods discussed are based on local piecewise-linear secant approximations to continuous conve...
We consider the linearly constrained separable convex programming, whose objective function is separ...
The equivalent formulation of a convex optimization problem is the computation of a value of a conju...
Convex programming has played an important role in studying a wide class of applications arising fro...
We discuss two models from the literature that have been developed to formulate piecewise linear app...
The assumed global optimum solution obtained in linear programming is not an assumed characteristic ...
We consider N-fold 4-block decomposable integer programs, which simultaneously generalize N...
AbstractThe problem of minimizing a separable nonlinear objective function under linear constraints ...