Sequential, Quadratic Constrained, Quadratic Programming for General Nonlinear Programming

2000 ◽  
pp. 563-575 ◽  
Author(s):  
Serge Kruk ◽  
Henry Wolkowicz
Keyword(s):  
Nonlinear Programming ◽  
Quadratic Programming ◽  
General Nonlinear Programming

scholarly journals Evolutionary Algorithms for Constrained Parameter Optimization Problems

1996 ◽  
Vol 4 (1) ◽  
pp. 1-32 ◽  
Author(s):  
Zbigniew Michalewicz ◽  
Marc Schoenauer
Keyword(s):  
Nonlinear Programming ◽  
Evolutionary Algorithms ◽  
Evolutionary Computation ◽  
Numerical Optimization ◽  
Optimization Problems ◽  
Optimization Techniques ◽  
Test Cases ◽  
Nonlinear Constraints ◽  
Nonlinear Programming Problem ◽  
General Nonlinear Programming

Evolutionary computation techniques have received a great deal of attention regarding their potential as optimization techniques for complex numerical functions. However, they have not produced a significant breakthrough in the area of nonlinear programming due to the fact that they have not addressed the issue of constraints in a systematic way. Only recently have several methods been proposed for handling nonlinear constraints by evolutionary algorithms for numerical optimization problems; however, these methods have several drawbacks, and the experimental results on many test cases have been disappointing. In this paper we (1) discuss difficulties connected with solving the general nonlinear programming problem; (2) survey several approaches that have emerged in the evolutionary computation community; and (3) provide a set of 11 interesting test cases that may serve as a handy reference for future methods.

scholarly journals PERBANDINGAN METODE SEPARABLE PROGRAMMING DAN QUADRATIC PROGRAMMING DALAM PEMECAHAN MASALAH PEMROGRAMAN NONLINIER

2019 ◽  
Vol 8 (4) ◽  
pp. 277
Author(s):  
I GEDE WIKAN ADIWIGUNA ◽  
G.K GANDHIADI ◽  
NI MADE ASIH
Keyword(s):  
Nonlinear Programming ◽  
Quadratic Programming ◽  
Linear Function ◽  
Nonlinear Model ◽  
Simplex Method ◽  
Programming Method ◽  
Single Variable ◽  
Separable Programming ◽  
Quadratic Programming Method

The Separable programming method solves nonlinear programming problems by transforming a nonlinear shape that consists of a single variable into a linear function and resolved by the simplex method. Meanwhile, the quadratic programming method accomplishes the two degrees nonlinear model by transforming the nonlinear shape into linear function with the Kuhn Tucker Conditions and resolved by the simplex Wolfe method. Both of these methods are applied to the Markowitz’s portfolio model, which is to find the proportion of stock funds to obtain maximum profits by combination of three shares, such as BMRI, GGRM, and ICBP. The completion using the quadratic programming method is more effective and efficient with the same optimum value.

Enhancing Infeasibility Detection Method for Mechanical Design Problems

2013 ◽  
Author(s):  
E. Khorshid ◽  
A. Falah
Keyword(s):  
Nonlinear Programming ◽  
Quadratic Programming ◽  
Sequential Quadratic Programming ◽  
Detection Method ◽  
Mechanical Design ◽  
Starting Point ◽  
Real Performance ◽  
Infeasibility Detection ◽  
Complex Mechanical Systems ◽  
Initial Starting

This paper presents the application of the Multistart point technique in order to enhance a previous existing infeasibility detection method based on Sequential Quadratic Programming (SQP) used for detecting modeling errors by finding the Minimum Intractable Subsystem (MIS) of constraints. This new method showed a great potential in detecting infeasibility without countering the problems of the initial starting point faced by many methods for Nonlinear Programming Problems. The real performance of the anticipated method is demonstrated by solving complex mechanical systems were inconsistency constraints are presented. The proposed method succeeded to find the MIS set of constraints that cause infeasibility in the these models while direct Nonlinear Programming solver, based on Sequential Quadratic Programming only, failed to detect the correct inconsistent constraints.

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