Finite?-subgradient algorithm for approximate solution of the parametric programming problem

1992 ◽  
Vol 3 (1) ◽  
pp. 39-43
Author(s):  
S. K. Zavriev
Keyword(s):  
Approximate Solution ◽  
Programming Problem ◽  
Parametric Programming ◽  
Subgradient Algorithm

scholarly journals Best Proximity Points for Some Classes of Proximal Contractions

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Maryam A. Alghamdi ◽  
Naseer Shahzad ◽  
Francesca Vetro
Keyword(s):  
Approximate Solution ◽  
Nonlinear Programming ◽  
Programming Problem ◽  
Iterative Algorithm ◽  
Best Proximity Point ◽  
Sufficient Conditions ◽  
Nonlinear Programming Problem ◽  
Optimal Approximate Solution ◽  
Unique Point ◽  
Banach’S Contraction Principle

Given a self-mapping and a non-self-mapping , the aim of this work is to provide sufficient conditions for the existence of a unique point , calledg-best proximity point, which satisfies . In so doing, we provide a useful answer for the resolution of the nonlinear programming problem of globally minimizing the real valued function , thereby getting an optimal approximate solution to the equation . An iterative algorithm is also presented to compute a solution of such problems. Our results generalize a result due to Rhoades (2001) and hence such results provide an extension of Banach's contraction principle to the case of non-self-mappings.

scholarly journals Fundamental Solution Method in a few MATLAB lines

2017 ◽  
Author(s):  
Agah D. Garnadi
Keyword(s):  
Approximate Solution ◽  
Fundamental Solution ◽  
Quadratic Programming ◽  
Programming Problem ◽  
Solution Method ◽  
Quadratic Programming Problem ◽  
Fundamental Solution Method

We report a computational exposition to approximate solution of Laplaceequation on the plane using Fundamental Solution Method. For agiven boundary conditionsat the boundary, we recoverthe approximate solution in the region. We demonstrate thatfundamental solution method for the model leads to anunconstrained Quadratic Programming problem. To address the issue ofill-conditioning, we suggests to use SVD to overcome this issue.The implementation of the methods is using MATLAB.

Batch Process and Sensitivity Analysis of Collision Detection of Planar Convex Polygons in Motion

2013 ◽  
Vol 13 (4) ◽  
Author(s):  
Cheng-fu Chen
Keyword(s):  
Sensitivity Analysis ◽  
Programming Problem ◽  
Collision Detection ◽  
Parametric Programming ◽  
Batch Process ◽  
Detection Problem ◽  
Convex Polygons ◽  
Parametric Problem ◽  
Decomposition Procedure ◽  
Two Parameters

A new method for formulation, solution, and sensitivity analysis of collision detection of convex objects in motion is presented. The collision detection problem is formulated as a parametric programming problem governed by the changes in the relative translation and relative rotation between the two objects considered. The two parameters together determine all the possible relative configurations between two moving convex objects. Therefore, solving this parametric problem allows for knowing the proximity information for all the possible configurations of the objects. We develop a two-step decomposition procedure to solve this parametric programming problem, and show that the solution is a convex function of the two parameters. This convexity feature enables an archive of the proximity information and sensitivity analysis for the collision detection problem.

Solving Non-Linear Bi-Level Programming Problem Using Taylor Algorithm

2016 ◽  
pp. 797-810
Author(s):  
Eghbal Hosseini ◽  
Isa Nakhai Kamalabadi ◽  
Fatemah Daneshfar
Keyword(s):  
Approximate Solution ◽  
Programming Problem ◽  
Feasible Solution ◽  
Test Problems ◽  
Hard Problem ◽  
Np Hard ◽  
Approximate Methods ◽  
Finance Management ◽  
Non Linear ◽  
Np Hard Problem

In recent years the bi-level programming problem (BLPP) is interested by many researchers and it is known as an appropriate tool to solve the real problems in several areas such as economic, traffic, finance, management and so on. Also it has been proved that the general BLPP is an NP-hard problem. The literature shows a few attempts for using approximate methods. In this chapter we attempt to develop an effective approach based on Taylor theorem to obtain an approximate solution for the non-linear BLPP. In this approach using the Karush-Kuhn–Tucker, the BLPP has been converted to a non-smooth single problem, and then it is smoothed by the Fischer – Burmeister function. Finally the smoothed problem is solved using an approach based on Taylor theorem. The presented approach achieves an efficient and feasible solution in an appropriate time which is evaluated by comparing to references and test problems.

scholarly journals An Approximate Solution of some Variational Problems Using Boubaker Polynomials

2018 ◽  
Vol 15 (1) ◽  
pp. 106-109 ◽  
Author(s):  
Baghdad Science Journal
Keyword(s):  
Approximate Solution ◽  
Quadratic Programming ◽  
Variational Problem ◽  
Programming Problem ◽  
Variational Problems ◽  
Quadratic Programming Problem ◽  
Numerical Examples ◽  
Boubaker Polynomials

In this paper, an approximate solution of nonlinear two points boundary variational problem is presented. Boubaker polynomials have been utilized to reduce these problems into quadratic programming problem. The convergence of this polynomial has been verified; also different numerical examples were given to show the applicability and validity of this method.

Approximate Solution of One Dynamic Problem of Geoinformatics

2010 ◽  
Vol 42 (5) ◽  
pp. 1-11 ◽  
Author(s):  
Vladimir M. Bulavatskiy ◽  
Vasiliy V. Skopetsky
Keyword(s):  
Approximate Solution ◽  
Dynamic Problem
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