Advanced engineered-conditioning genetic approach to power economic dispatch

Abstract

Computational efficiency and reliability are the major concerns in the application of genetic algorithms (GAS) to practical problems. Effort has been made in two directions to improve the performance of GAs: the investigation of advanced genetic operators and the development of genetic algorithm hybrids. In this paper, an advanced engineered-conditioning genetic algorithm hybrid (AEC-GA) is proposed, which is a combination strategy involving local search algorithms and genetic algorithms. Moreover, several advanced techniques which enhance program efficiency and accuracy, such as elite policy, adaptive mutation prediction, nonlinear fitness mapping and different crossover techniques, are explored. Using power economic dispatch problems as a basis for comparisons, the outcome of the study clearly demonstrates the advantages of the AEC-GA.