The aim of paper is to apply two types of particle swarm optimization, global best andlocal best PSO to a constrained maximum likelihood estimation problem in pseudotime anal-ysis, a sub-field in bioinformatics. The results have shown that particle swarm optimizationis extremely useful and efficient when the optimization problem is non-differentiable and non-convex so that analytical solution can not be derived and gradient-based methods can not beapplied.

中文翻译：

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约束最大似然估计中的粒子群优化算法

本文的目的是将两种类型的粒子群优化方法，即全局最优和局部最优粒子群优化应用于生物信息学子领域的伪时间分析中的约束最大似然估计问题。结果表明，当优化问题是不可微且非凸的时，粒子群算法是非常有用和高效的，因此无法导出解析解，也无法应用基于梯度的方法。