DocumentCode
2806850
Title
A Hybrid Vector Artificial Physics Optimization for Constrained Optimization Problems
Author
Xie, Liping ; Zeng, Jianchao
Author_Institution
Complex Syst. & Comput. Intell. Lab., Taiyuan Univ. of Sci. & Technol., Taiyuan, China
fYear
2011
fDate
21-23 Nov. 2011
Firstpage
145
Lastpage
148
Abstract
Artificial physics optimization algorithm (APO) is used to solve constrained optimization problem. A 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 ensure that the moving of the whole population is limited in the feasible region. 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; constrained optimization problems; decision space; diagonal matrix; hybrid vector artificial physics optimization; multidimensional search method; shrinkage coefficient; Force; Optimization; Search problems; Upper bound; Vectors; APO; Artificial physics optimization; constrained optimization problem; multi-dimensional search methods;
fLanguage
English
Publisher
ieee
Conference_Titel
Robot, Vision and Signal Processing (RVSP), 2011 First International Conference on
Conference_Location
Kaohsiung
Print_ISBN
978-1-4577-1881-6
Type
conf
DOI
10.1109/RVSP.2011.68
Filename
6114925
Link To Document