IEEE International Conference on Evolutionary Computations , 2008-06-01

Title : ( Magnetic Optimization Algorithms, a New Synthesis )

Authors: محمد طیرانی , Mohammad Reza Akbarzadeh Totonchi ,

Citation: BibTeX | EndNote

Abstract—A novel optimization algorithm is proposed here that is inspired by the principles of magnetic field theory. In the proposed Magnetic Optimization Algorithm (MOA) the possible solutions are magnetic particles scattered in the search space. Each magnetic particle has a measure of mass and magnetic field according to its fitness. The fitter magnetic particles are those with higher magnetic field and higher mass. These particles are located in a lattice-like environment and apply a force of attraction to their neighbors. The proposed cellular structure allows a better exploitation of local neighborhoods before they move towards the global best, hence it increases population diversity. Experimental results on 14 numerical benchmark functions show that MOA in some benchmark functions can work better than GA and PSO.

Keywords

برای دانلود از شناسه و رمز عبور پرتال پویا استفاده کنید.

@inproceedings{paperid:1007735,
author = {محمد طیرانی and Akbarzadeh Totonchi, Mohammad Reza},
title = {Magnetic Optimization Algorithms, a New Synthesis},
booktitle = {IEEE International Conference on Evolutionary Computations},
year = {2008},
keywords = {.},
}

[Download]

%0 Conference Proceedings
%T Magnetic Optimization Algorithms, a New Synthesis
%A محمد طیرانی
%A Akbarzadeh Totonchi, Mohammad Reza
%J IEEE International Conference on Evolutionary Computations
%D 2008

[Download]