Title :
A novel optimization algorithm: space gravitational optimization
Author :
Hsiao, Ying-Tung ; Chuang, Cheng-Long ; Jiang, Joe-Air ; Chien, Cheng-Chih
Author_Institution :
Dept. of Electr. Eng., Tamkang Univ., Taipei, Taiwan
Abstract :
A new concept for the optimization of nonlinear functions is proposed. For most of the proposed evolutionary optimization algorithms, such as particle swarm optimization and ant colony optimization, they search the solution space by sharing known knowledge. The proposed algorithm is based on the Einstein´s general theory of relativity, which we utilize the concept of gravitational field to search for the global optimal solution for a given problem. In this paper, detail procedure of the proposed algorithm is introduced. The proposed algorithm has been tested on an application that is known difficult with promising and exciting results.
Keywords :
control system synthesis; evolutionary computation; optimisation; search problems; three-term control; Einstein relativity theory; PID controller design; ant colony optimization; evolutionary optimization algorithms; nonlinear function optimization; particle swarm optimization; space gravitational optimization; Algorithm design and analysis; Ant colony optimization; Astrophysics; Birds; Design optimization; Particle swarm optimization; Physics; Simulated annealing; Testing; Three-term control; Einstein’s general theory of relativity; Optimization theory; PID controller; gravitational field;
Conference_Titel :
Systems, Man and Cybernetics, 2005 IEEE International Conference on
Print_ISBN :
0-7803-9298-1
DOI :
10.1109/ICSMC.2005.1571495
