Title :
A Hybrid Vector Artificial Physics Optimization with Multi-dimensional Search Method
Author :
Xie, Liping ; Zeng, Jianchao ; Cai, Xingjuan
Author_Institution :
Complex Syst. & Comput. Intell. Lab., Taiyuan Univ. of Sci. & Technol., Taiyuan, China
Abstract :
Artificial physics optimization algorithm (APO) is a new swarm intelligence algorithm to solve global optimization problem based on Physicomimetics framework. An n order diagonal matrix of shrinkage coefficient is introduced to ensure that each individual is within the decision space. Multi-dimensional search method is merged into the vector model of APO to improve the local exploitation capability of vector APO. The simulation results confirm that the performance of the hybrid vector APO with multi-dimensional search method is effective.
Keywords :
matrix algebra; optimisation; search problems; decision space; diagonal matrix; global optimization problem; hybrid vector artificial physics optimization algorithm; local exploitation capability; multidimensional search method; physicomimetics framework; shrinkage coefficient; swarm intelligence algorithm; Benchmark testing; Force; Optimization; Search problems; Vectors; APO; Artificial physics optimization; global optimization problem; multi-dimensional search methods;
Conference_Titel :
Innovations in Bio-inspired Computing and Applications (IBICA), 2011 Second International Conference on
Conference_Location :
Shenzhan
Print_ISBN :
978-1-4577-1219-7
DOI :
10.1109/IBICA.2011.33
