Add to ORKGWe propose an exact penalty approach for solving mixed integer nonlinear programming (MINLP) problems by converting a general MINLP problem to a finite sequence of nonlinear programming (NLP) problems with only continuous variables. We express conditions of exactness for MINLP problems and show how the exact penalty approach can be extended to constrained problems
We introduce the concept of partially strictly monotone functions and apply it to construct a class ...
This paper presents a penalty approach for globally solving nonsmooth and nonconvex mixed-integer no...
We consider a class of nondifferentiable penalty functions associated to nonlinear programming probl...
A practical comparison of penalty functions for globally solving mixed-integer nonlinear programming...
In this work, we study exact continuous reformulations of nonlinear integer programming problems. To...
In this work, we study exact continuous reformulations of nonlinear integer programming problems. To...
In this work, we study exact continuous reformulations of nonlinear integer programming problems. To...
In this work, we propose a global optimization approach for mixed-integer programming problems. To t...
Abstract. Many optimization problems involve integer and continuous variables that can be modeled as...
Abstract. We consider the following classes of nonlinear programming problems: the minimization of s...
In this paper, we consider a general class of nonlinear mixed discrete programming problems. By intr...
In this article, we aim to extend the firefly algorithm (FA) to solve bound constrained mixed-intege...
A penalty framework for globally solving mixed-integer nonlinear programming problems is presented. ...
A practical comparison of penalty functions for globally solving mixed-integer nonlinear programming...
We introduce the concept of partially strictly monotone functions and apply it to construct a class ...
We introduce the concept of partially strictly monotone functions and apply it to construct a class ...
This paper presents a penalty approach for globally solving nonsmooth and nonconvex mixed-integer no...
We consider a class of nondifferentiable penalty functions associated to nonlinear programming probl...
A practical comparison of penalty functions for globally solving mixed-integer nonlinear programming...
In this work, we study exact continuous reformulations of nonlinear integer programming problems. To...
In this work, we study exact continuous reformulations of nonlinear integer programming problems. To...
In this work, we study exact continuous reformulations of nonlinear integer programming problems. To...
In this work, we propose a global optimization approach for mixed-integer programming problems. To t...
Abstract. Many optimization problems involve integer and continuous variables that can be modeled as...
Abstract. We consider the following classes of nonlinear programming problems: the minimization of s...
In this paper, we consider a general class of nonlinear mixed discrete programming problems. By intr...
In this article, we aim to extend the firefly algorithm (FA) to solve bound constrained mixed-intege...
A penalty framework for globally solving mixed-integer nonlinear programming problems is presented. ...
A practical comparison of penalty functions for globally solving mixed-integer nonlinear programming...
We introduce the concept of partially strictly monotone functions and apply it to construct a class ...
We introduce the concept of partially strictly monotone functions and apply it to construct a class ...
This paper presents a penalty approach for globally solving nonsmooth and nonconvex mixed-integer no...
We consider a class of nondifferentiable penalty functions associated to nonlinear programming probl...