计算机科学与探索2019，Vol.13Issue(9)：1567-1581,15.
微生物动力学优化算法
Microbial Dynamics Optimization Algorithm??
摘要
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.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Key words
swarm intelligence optimization algorithm/ microbial culture kinetics/ microbial population/ microbial dynamics optimization (MDO) algorithm分类
信息技术与安全科学引用本文复制引用
陆秋琴,黄光球..微生物动力学优化算法[J].计算机科学与探索,2019,13(9):1567-1581,15.基金项目
The National Natural Science Foundation of China under Grant No. 71874134 (国家自然科学基金) （国家自然科学基金）
the Key Project of Natural Sci-ence Basic Research Plan of Shaanxi Province under Grant No. 2019JZ-30 (陕西省自然科学基础研究计划-重点项目) （陕西省自然科学基础研究计划-重点项目）
the Social Science Fund Project of Shaanxi Province under Grant Nos. 2017S035, 2018S49 (陕西省社会科学基金项目) （陕西省社会科学基金项目）
the Industrialization Project of Shaanxi Provincial Department of Education under Grant No. 16JF015 (陕西省教育厅服务地方专项计划项目). （陕西省教育厅服务地方专项计划项目）
