Title :
PSO with Constraint-Preserving Mechanism for Mixed-Variable Optimization Problems
Author :
Sun, Chaoli ; Zeng, Jianchao ; Pan, Jengshyang ; Zhang, Yunqiang
Author_Institution :
Complex Syst. & Comput. Intell. Lab., Taiyuan Univ. of Sci. & Technol., Taiyuan, China
Abstract :
A new algorithm (called CPMPSO for short), in which PSO with constraint-preserving mechanism is used as a global search algorithm and PSO itself is used as local search one, is proposed in this paper to solve mixed-variable optimization problems. The values of non-continuous variables are got according to the velocity of the particle, the constraint-preserving method is used as the mechanism for handling the constraint violations, and the particle swarm optimization itself is used as local search algorithm to obtain the consistent optimal results for mixed-variable optimization problems. The performance of CPMPSO is evaluated against two real-world mixed-variable optimization problems, and it is found to be highly competitive compared with other existing algorithms.
Keywords :
constraint theory; particle swarm optimisation; search problems; CPMPSO; constraint-preserving mechanism; global search algorithm; mixed-variable optimization problems; Genetic algorithms; Optimization; Particle swarm optimization; Programming; Springs; Stochastic processes; constraint-preserving; mixed-variable optimization problems; particle swarm optimization;
Conference_Titel :
Robot, Vision and Signal Processing (RVSP), 2011 First International Conference on
Conference_Location :
Kaohsiung
Print_ISBN :
978-1-4577-1881-6
DOI :
10.1109/RVSP.2011.32