The general constrained polynomial programming problem (GPP) is considered in this paper. Problem (GPP) has a broad range of applications and is proved to be NP-hard. Necessary global optimality conditions for problem (GPP) are established. Then, a new local optimization method for this problem is proposed by exploiting these necessary global optimality conditions. A global optimization method is proposed for this problem by combining this local optimization method together with an auxiliary function. Some numerical examples are also given to illustrate that these approaches are very efficient. (C) 2015 Elsevier Inc. All rights reserved
A large number of nonlinear optimization problems involve bilinear, quadratic and/or polynomial func...
Global optimization is a branch of mathematical programming with fewer computational techniques and ...
We present a novel efficient theoretical and numerical framework for solving global non-convex polyn...
The polynomial programming problem which has a polynomial objective function, either with no constra...
This paper is concerned with the general polynomial programming problem with box constraints, includ...
Abstract In this paper, we develop necessary conditions for global optimality that apply to non-line...
In this paper, some verifiable necessary global optimality conditions and sufficient global optimali...
In this paper we present necessary conditions for global optimality for polyno-mial problems over bo...
Abstract. A deterministic global optimization approach is proposed for nonconvex constrained nonline...
The goal of this thesis is to study a special nonlinear programming, namely, polynomial optimization...
Multivariate cubic polynomial optimization problems, as a special case of the general polynomial opt...
In this paper multivariate quartic polynomial optimization program (QPOP) is considered. Quartic opt...
Minimizing a polynomial function over a region defined by polynomial inequalities models broad class...
In this paper, we propose an algorithm for constrained global optimization of mixed-integer nonlinea...
Global optimization is a branch of mathematical programming with fewer computational techniques and ...
A large number of nonlinear optimization problems involve bilinear, quadratic and/or polynomial func...
Global optimization is a branch of mathematical programming with fewer computational techniques and ...
We present a novel efficient theoretical and numerical framework for solving global non-convex polyn...
The polynomial programming problem which has a polynomial objective function, either with no constra...
This paper is concerned with the general polynomial programming problem with box constraints, includ...
Abstract In this paper, we develop necessary conditions for global optimality that apply to non-line...
In this paper, some verifiable necessary global optimality conditions and sufficient global optimali...
In this paper we present necessary conditions for global optimality for polyno-mial problems over bo...
Abstract. A deterministic global optimization approach is proposed for nonconvex constrained nonline...
The goal of this thesis is to study a special nonlinear programming, namely, polynomial optimization...
Multivariate cubic polynomial optimization problems, as a special case of the general polynomial opt...
In this paper multivariate quartic polynomial optimization program (QPOP) is considered. Quartic opt...
Minimizing a polynomial function over a region defined by polynomial inequalities models broad class...
In this paper, we propose an algorithm for constrained global optimization of mixed-integer nonlinea...
Global optimization is a branch of mathematical programming with fewer computational techniques and ...
A large number of nonlinear optimization problems involve bilinear, quadratic and/or polynomial func...
Global optimization is a branch of mathematical programming with fewer computational techniques and ...
We present a novel efficient theoretical and numerical framework for solving global non-convex polyn...