Research on New Intelligent Optimization Algorithm Based on the Law of Universal Gravitation

DOI

10.2991/cimns-18.2018.27How to use a DOI?

Keywords

global optimization; gravitation; numerical experiments; crank rocker

Abstract

In order to solve the problem of global optimization, a new optimization method based on the law of universal gravitation is proposed, which is a random search algorithm derived from the simulation of natural imagination, which belongs to the category of evolutionary computation and is a new intelligent optimization algorithm. This method abstracts the global optimal value into a "black hole" in the universe, and other free celestial bodies in the universe approach the "black hole" by gravitational force, and are eventually "swallowed" by the black hole. The direction and step of the algorithm iteration are deduced through the formula of gravitation, which reduces the influence of the stochastic factors on the algorithm and improves the efficiency of the optimization calculation. Through numerical experiments, it is proved that the performance of the algorithm in global convergence and computing speed is superior to other optimization algorithms in the relevant literatures, and the specular reflection algorithm is also proven to be an effective and reliable optimization tool when solving high-dimensional optimization problems. It is applied to the optimization design of crank and rocker mechanism, and the calculation result further affirms the value of the algorithm in the field of engineering calculation.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Zhong Ren
AU  - Qisong Qi
AU  - Qing Dong
AU  - Gening Xu
PY  - 2018/11
DA  - 2018/11
TI  - Research on New Intelligent Optimization Algorithm Based on the Law of Universal Gravitation
BT  - Proceedings of the 2018 3rd International Conference on Communications, Information Management and Network Security (CIMNS 2018)
PB  - Atlantis Press
SP  - 118
EP  - 123
SN  - 2352-538X
UR  - https://doi.org/10.2991/cimns-18.2018.27
DO  - 10.2991/cimns-18.2018.27
ID  - Ren2018/11
ER  -