Title :
Artificial Plant Optimization Algorithm for Constrained Optimization Problems
Author :
Zhao, Ziqiang ; Cui, Zhihua ; Zeng, Jianchao ; Yue, Xiaoguang
Author_Institution :
Complex Syst. & Comput. Intell. Lab., Taiyuan Univ. of Sci. & Technol., Taiyuan, China
Abstract :
Artificial plant optimization algorithm is proposed to solve constrained optimization problems in this paper. In APOA, a shrinkage coefficient is introduce to ensure that all dimensions of a branch are within lower and upper bounds, and a new function to determine whether the particle is within the feasible region. One dimensional search optimization methods are selected in algorithm to produce a new position which is guaranteed to be in the feasible region for the branch which escapes from the feasible region. The experimental results show that artificial plant optimization algorithm is effective and efficient for constrained optimization problems.
Keywords :
constraint theory; optimisation; search problems; artificial plant optimization algorithm; constrained optimization problems; search optimization; shrinkage coefficient; Algorithm design and analysis; Educational institutions; Optimization methods; Particle swarm optimization; Search problems; Upper bound; artificial plant optimization algorithm; constraint; feasible region; shrinkage coefficient;
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.2011.34
