A Novel Optimization Algorithm: Space Gravitational Optimization
Ying-Tung Hsiao, Cheng-Long Chuang, Joe‐Air Jiang, Cheng-Chih Chien · 2006
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.