In this study a hybrid (including qualitative and quantitative objectives) fuzzy multi objective nonlinear programming (H-FMONLP) model with different goal priorities will be developed for aggregate production planning (APP) problem in a fuzzy environment. Using an interactive decision making process the proposed model tries to minimize total production costs, carrying and back ordering costs a...

In recent years, many traditional optimization methods have been successfully generalized to minimize objective functions on manifolds. In this paper, we first extend the general traditional constrained optimization problem to a nonlinear programming problem built upon a general Riemannian manifold M , and discuss the first-order and the second-order optimality conditions. By exploiting the dif...

In this paper we interpret chaos synchronization schemes within the framework of Lagrange programming networks, which form a class of continuous-time optimization methods for solving constrained nonlinear optimization problems. From this study it follows that standard synchronization schemes can be regarded as a Lagrange programming network with soft constraining, where synchronization between ...

A line search method is proposed for nonlinear programming using Fletcher and Leyffer’s filter method, which replaces the traditional merit function. Global convergence properties of this method was analyzed in a companion paper. Here a simple modification of the method introducing second order correction steps is presented. It is shown that the proposed method does not suffer from the Maratos ...

In this paper we consider the problem of solving a special class of nonlinear constrained optimization problems. The study of this class of problems has been motivated by a practical application, namely the railway yield management problem. The aim of this paper is to deene a nonlinear minimization algorithm which exploits as much as possible the structure of the problems under consideration. T...

In this report we describe a comparison of different algorithms for solving nonlinear optimization problems with simple bounds on the variables. Moreover, we would like to come out with an assessment of the optimization library DOT used in the optimization suite OPTALIA at Airbus for this kind of problems.

We present an algorithm that achieves superlinear convergence for nonlinear programs satisfying the Mangasarian-Fromovitz constraint qualiication and the quadratic growth condition. This convergence result is obtained despite the potential lack of a locally convex augmented Lagrangian. The algorithm solves a succession of subproblems that have quadratic objective and quadratic constraints, both...

This paper presents algorithms for optimal development (flattening) of a smooth continuous curved surface embedded in three-dimensional space into a planar shape. The development process is modeled by in-plane strain (stretching) from the curved surface to its planar development. The distribution of the appropriate minimum strain field is obtained by solving a constrained nonlinear programming ...

This paper describes an active set algorithm for large scale nonlinear programming based on the successive linear programming method proposed by Fletcher and Sainz de la Maza The step computation is performed in two stages In the rst stage a linear program is solved to estimate the active set at the solution The linear program is obtained by making a linear approximation to the penalty function...