Title :
A new genetic algorithm for nonlinear programming problems
Author :
Jiafu Tang ; Dingwei Wang
Author_Institution :
Sch. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
Abstract :
A special genetic algorithm with mutation along the weighted gradient direction for nonlinear programming problems is proposed. It uses penalty function to construct fitness function for evaluating the solution which violates the constraints. The convergence analysis of the method are also given in this paper.
Keywords :
convergence of numerical methods; genetic algorithms; nonlinear programming; convergence; fitness function; genetic algorithm; nonlinear programming; penalty function; weighted gradient direction; Algorithm design and analysis; Constraint optimization; Decoding; Functional programming; Genetic algorithms; Genetic engineering; Genetic mutations; Information science; Optimization methods;
Conference_Titel :
Decision and Control, 1997., Proceedings of the 36th IEEE Conference on
Conference_Location :
San Diego, CA, USA
Print_ISBN :
0-7803-4187-2
DOI :
10.1109/CDC.1997.649813
