关键词: 群智能优化算法, 微生物培养动力学, 微生物种群, 微生物动力学优化（MDO）算法

Abstract: In order to solve a class of function optimization problems, a population intelligent optimization algorithm, microbial dynamics optimization (MDO) algorithm, is proposed by using the microbial culture dynamics with hybrid food chain and time delay. In this algorithm, it is assumed that many microbial populations are cultivated in a microbiological culture system, the growth of microbial populations is influenced not only by the flow of culture fluid and the concentration of nutrients and harmful substances in the culture system, but also by the interaction of populations; the regular injection of the culture medium will suddenly increase the concentration of nutrients and toxic substances, which will suddenly increase the impact on populations. Using these characteristics, the absorption operator, the snatching operator, the hybrid operator and the toxin operator are constructed; by use of these operators and the growth and changes of microbial populations, the global optimal solutions of an optimization problem can be quickly determined. The simulation results show that the MDO algorithm has certain advantages in solving opti-mization problems with higher dimensions.

Key words: swarm intelligence optimization algorithm, microbial culture kinetics, microbial population, microbial dynamics optimization (MDO) algorithm