نتایج جستجو برای: nonlinear programming nlp

تعداد نتایج: 542890  

2007
Christopher Amato Daniel S. Bernstein Shlomo Zilberstein

In this paper, we discuss a new approach that represents POMDP policies as finite-state controllers and formulates the optimal policy of a desired size as a nonlinear program (NLP). This new representation allows a wide range of powerful nonlinear programming algorithms to be used to solve POMDPs. Although solving the NLP optimally is often intractable, the results we obtain using an off-theshe...

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه بوعلی سینا - دانشکده علوم پایه 1391

abstract: in this thesis, we focus to class of convex optimization problem whose objective function is given as a linear function and a convex function of a linear transformation of the decision variables and whose feasible region is a polytope. we show that there exists an optimal solution to this class of problems on a face of the constraint polytope of feasible region. based on this, we dev...

Journal: :Int. J. Comput. Math. 2011
M. Teresa T. Monteiro José Filipe P. Meira

The goal of this paper is to solve Mathematical Program with Complementarity Constraints (MPCC) using nonlinear programming (NLP) techniques. This work presents two algorithms based on several nonlinear techniques such as Sequential Quadratic Programming (SQP), penalty techniques and regularization schemes. A set of AMPL problems were tested and the computational experience shows that both algo...

2011
Roohollah Aliakbari Shandiz Nezam Mahdavi-Amiri

We 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.

2009
Victor M. Zavala Lorenz T. Biegler L. T. Biegler

Sensitivity-based strategies for on-line moving horizon estimation (MHE) and nonlinear model predictive control (NMPC) are presented both from a stability and computational perspective. These strategies make use of full-space interior-point nonlinear programming (NLP) algorithms and NLP sensitivity concepts. In particular, NLP sensitivity allows us to partition the solution of the optimization ...

2007
M. Ropotar Z. Kravanja

This contribution describes the development of various strategies for the dynamic optimization of a batch reactor in order to obtain a robust model, suitable for nonlinear (NLP) or mixed-integer nonlinear programming (MINLP) problems. Different Orthogonal Collocation on Finite Element (OCFE) schemes and various formulations of the MINLP model have been studied to increase its robustness. It has...

2006
Helena Sofia Rodrigues

S u m m a r y. MPCC can be solved with specific MPCC codes or in its nonlinear equivalent formulation (NLP) using NLP solvers. Two NLP solvers-NPSOL and the line search filter SQP-are used to solve a collection of test problems in AMPL. Both are based on SQP (Sequential Quadratic Programming) philosophy but the second one uses a line search filter scheme.

1999
Arturo M. Cervantes Andreas Wachter Reha H. T Lorenz T. Biegler

A novel nonlinear programming (NLP) strategy is developed and applied to the optimization of diierential algebraic equation (DAE) systems. Such problems, also referred to as dynamic optimization problems, are common in chemical process engineering and remain challenging applications of nonlinear programming. These applications often consist of large, complex nonlinear models that result from di...

Journal: :Applied Mathematics and Computer Science 2011
Wojciech Szynkiewicz Jacek Blaszczyk

An application of advanced optimization techniques to solve the path planning problem for closed chain robot systems is proposed. The approach to path planning is formulated as a “quasi-dynamic” NonLinear Programming (NLP) problem with equality and inequality constraints in terms of the joint variables. The essence of the method is to find joint paths which satisfy the given constraints and min...

This paper describes a low computational direct approach for optimal motion planning and obstacle avoidance of Omni-directional mobile robots within velocity and acceleration constraints on the robot motion. The main purpose of this problem is the minimization of a quadratic cost function while limitation on velocity and acceleration of robot is considered and collision with any obstacle in the...

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