Title :
Stochastic Optimization Problem through Particle Swarm Optimization Algorithm
Author :
He, Fangguo ; Chen, Wenlue
Author_Institution :
Coll. of Math. & Inf. Sci., Huanggang Normal Univ., Huanggang
Abstract :
In this paper, two classes of stochastic optimization problems, which are expected value models and chance-constrained programming, are introduced. In order to solve the problems, the method of stochastic simulation is used to generate training samples for neural network, and then particle swarm optimization algorithm and neural network are integrated to produce a hybrid intelligent algorithm. Two numerical examples are provided to illustrate the effectiveness of the hybrid particle swarm optimization algorithm.
Keywords :
constraint handling; learning (artificial intelligence); neural nets; particle swarm optimisation; stochastic programming; chance constrained programming; neural network; particle swarm optimization; stochastic optimization problem; training sample; Constraint optimization; Functional programming; Intelligent networks; Modeling; Neural networks; Optimization methods; Particle swarm optimization; Stochastic processes; Stochastic systems; Uncertainty; Neural network; Particle swarm optimization; Stochastic optimization; Stochastic simulation;
Conference_Titel :
Networks Security, Wireless Communications and Trusted Computing, 2009. NSWCTC '09. International Conference on
Conference_Location :
Wuhan, Hubei
Print_ISBN :
978-1-4244-4223-2
DOI :
10.1109/NSWCTC.2009.355
