Optimization of feeding rate for alcohol fermentation by quantum-behaved Particle Swarm Optimization

Abstract

Quantum-behaved Particle Swarm Optimization (QPSO) algorithm is a global convergence guaranteed search method, which introduced quantum theory into traditional Particle Swarm Optimization (PSO). QPSO algorithm outperforms traditional PSO algorithm in search ability as well as having less parameter. In this paper, we employ QPSO algorithm to optimize the feeding rate of alcohol fermentation with the data of alcohol fermentation process. The simulation results show that QPSO algorithm can find better feeding rate quickly and yield more 4% output than traditional PSO algorithm.