@inproceedings{f0426acff31142e2abeef165f2646fa6,
title = "Genetic operators design using division algorithm in the integer solution space",
abstract = "Genetic algorithm (GA) is a well known algorithm applied to a wide variety of optimization problems [4]. It combines selection, crossover, and mutation operators in order to find the best solution to a problem. The standard GA operates on chromosomes represented by binary code strings [1, 2]. This paper designs alternative operators in the GA process. The new operations reduce the binary decoding process of chromosomes when performing the computation. Variations of solutions with the implemented operations on chromosomes are studied. Computational examples show that the new methods save the computer time and enhance the efficiency when compared to the standard GA.",
keywords = "Crossover, Genetic operator/algorithm, Mutation, Selection",
author = "Li Guiting and Wang Bingtuan and Li Aihua",
year = "2006",
language = "English",
isbn = "0889865949",
series = "Proceedings of the IASTED International Conference on Modelling and Simulation",
pages = "286--290",
booktitle = "Proceedings of the 17th IASTED International Conference on Modelling and Simulation",
note = "17th IASTED International Conference on Modelling and Simulation ; Conference date: 24-05-2006 Through 26-05-2006",
}