A globally convergent version of Robinson's algorithm for general nonlinear programming problems without using derivatives

1981 ◽  
Vol 35 (2) ◽  
pp. 195-216 ◽  
Author(s):  
J. Bräuninger
Keyword(s):  
Nonlinear Programming ◽  
Globally Convergent ◽  
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 A globally convergent primal-dual interior-point filter method for nonlinear programming

2004 ◽  
Vol 100 (2) ◽  
pp. 379-410 ◽  
Author(s):  
Michael Ulbrich ◽  
Stefan Ulbrich ◽  
Lu�s N. Vicente
Keyword(s):  
Nonlinear Programming ◽  
Interior Point ◽  
Filter Method ◽  
Globally Convergent ◽  
Primal Dual
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