Genetic algorithms are founded upon the principle of evolution, ie, survival of the fittest.
Hence evolution programming techniques, based on genetic algorithms, are applicable to …

Abstract Genetic Algorithms (GAs) are innovative search algorithms based on natural
phenomena, whose main advantages lie in great robustness and problem independence …

In this paper, a knowledge based genetic algorithm (GA) for path planning of a mobile robot
is proposed, which uses problem-specific genetic algorithms for robot path planning instead …

This paper studies the application of a genetic algorithm to discrete-time optimal control
problems. Numerical results obtained here are compared with ones yielded by GAMS, a …

The major difficulty in applicability of genetic algorithms to various optimization problems is
the lack of general methodology for handling constraints. This paper discusses a new such …

Genetic algorithms (GAs) are stochastic adaptive algorithms whose search method is based
on simulation of natural genetic inheritance and Darwinian striving for survival. They can be …

Many interesting optimization problems have no known fast solution algorithms either
because their objective functions are complicated (and possibly discontinuous) or because …

An Indexed Bibliography of Genetic Algorithms: Years 1957-1993 Page 1 An Indexed
Bibliography of Genetic Algorithms: Years 1957-1993 compiled by Jarmo T. Alander …

This paper reports on a study of the effectiveness of penalty functions used with a standard
genetic algorithm to solve a problem with constraints. Twelve different penalty functions …

A new method of designing recursive and nonrecursive frequency sampling filters is
presented. We investigate the use of a hybrid real-coded genetic algorithm (GA) for …