根生群优化算法

针对全局优化问题,基于一类支持向量数据描述（SVDD）和已有的根系生长算法提出一种新的智能优化算法——根生群优化算法,将根系划分为主根群体和侧根群体。基于SVDD描述主根群体的生长行为,将土壤中养分浓度最高的位置作为全局优化的目标,构建了根系生长模型;分析了RGSO的数学模型,从理论上证明了RGSO的收敛性。在实验中,与当前最先进的其他三个算法进行综合比较,并观察了不同参数对优化效果的影响。实验结果验证了RGSO的收敛性和有效性,表明RGSO是一种解决全局优化问题的有效算法。

Root growth swarm optimization algorithm

Aiming at the global optimization problem, this paper proposed a new intelligent algorithm called RGSO, based on SVDD and the root algorithm existed. The root system differentiated into the taproot and the lateral root group. Inspired by this growth behavior, this paper described the growth behavior of the taproot tips based on SVDD. The algorithm constructed the root growth model, and used the point of the highest concentration of nutrients in the soil as the target of global optimization. This paper analyzed the mathematical model of RGSO, and proved its convergence theoretically. In the experiment, this paper compared RGSO with the other three advanced algorithms, and tested the optimization effect with different parameters. The result of the experiment verified the convergence and effectiveness of RGSO, and it indicates that RGSO is an effective algorithm to solve global optimization problem.