Nonlinear Knapsack Problems (NKP) are the alternative formulation for the multiple-choice knapsack problems. A powerful approach for solving NKP is dynamic programming which may obtain the global op-timal solution even in the case of discrete solution space for these problems. Despite the power of this solu-tion approach, it computationally performs very slowly when the solution space of the pr...

logistic network design is one of the most important strategic decisions in supply chain management that has recently attracted the attention of many researchers. transportation network design is then one of the most important fields of logistic network. this study is concerned with designing a multi-stage and multi-product logistic network. at first, a mixed integer nonlinear programming model...

Automized stabilization and control of computer-controlled nonlinear processes is considered. A new algorithm which constitutes a combination of Popov's and of Jury and Lee's stability criteria with a nonlinear programming approach is proposed. The algorithm is applied to a digitally controlled antenna tracking system and the operation is simulated on an IBM 360/91 computer. The solution involv...

This paper considers the solution of Mixed Integer Nonlinear Programming (MINLP) problems. Classical methods for the solution of MINLP problems decompose the problem by separating the nonlinear part from the integer part. This approach is largely due to the existence of packaged software for solving Nonlinear Programming (NLP) and Mixed Integer Linear Programming problems. In contrast, an integ...

An exact semidefinite linear programming (SDP) relaxation of a nonlinear semidefinite programming problem is a highly desirable feature because a semidefinite linear programming problem can efficiently be solved. This paper addresses the basic issue of which nonlinear semidefinite programming problems possess exact SDP relaxations under a constraint qualification. We do this by establishing exa...

We study the following model for a system the state of which is continuously observed. The set of possible states is a finite set {0, . . . , L}, where larger values represent increased states of deterioration from the “new condition” represented by state 0, to the “totally inoperative condition” of state L. Whenever the system changes state a decision has to be made as to whether it is renovat...

Purpose – The purpose of this paper is to focus on optimization of recycling of concrete from lightweight aggregates containing expanded glass and hard polyurethane (PU) and on the issue of importance of environmental management in constructions, to produce the new combination using rest, construction waste of concrete from lightweight aggregates and hard PU new raw components of concrete from ...

This work is an example of application of nonlinear programming to a problem of three-dimensional trajectory optimization for multistage launch vehicles for geostationary orbit missions. The main objective is to minimize fuel consumption or equivalently to maximize the payload. The launch vehicle considered here, Europa-II, consists of 5 thrust phases and 2 coast phases. Major parameters of the...

The constrained least-squares regularization of nonlinear ill-posed problems is a nonlinear programming problem for which trust-region methods have been developed. In this paper the convergence theory of one of those methods is addressed. It will be proved that, under suitable hypotheses, local (superlinear or quadratic) convergence holds and every accumulation point is second-order stationary.

using the mean-value theorem for integrals we tried to solved the nonlinear integral equations of hammerstein type . the mean approach is to obtain an initial guess with unknown coefficients for unknown function y(x). the procedure of this method is so fast and don't need high cpu and complicated programming. the advantages of this method are that we can applied for those integral equation...