Journal of Computer Science

Parameter Settings for New Generational Genetic Algorithms for Solving Global Optimization Problems

Siew Mooi Lim, Md. Nasir Sulaiman, Norwati Mustapha and Abu Bakar Md. Sultan

DOI : 10.3844/jcssp.2015.1025.1031

Journal of Computer Science

Volume 11, Issue 11

Pages 1025-1031

Abstract

This study operates within experimental design with two main tools of Taguchi method namely orthogonal array and signal to noise ratio to discover the optimal parameter settings for newly proposed generational genetic algorithms; they are Laplace Crossover-Scale Truncated Pareto Mutation (LX-STPM) and Rayleigh Crossover-Scale Truncated Pareto Mutation (RX-STPM). It concluded that GA parameter settings are algorithms and problems dependent.

Copyright

© 2015 Siew Mooi Lim, Md. Nasir Sulaiman, Norwati Mustapha and Abu Bakar Md. Sultan. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.