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An improved genetic algorithm for optimization of chemical process

机译:用于化学过程优化的改进遗传算法

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Genetic algorithm (GA) is widely used because it is an efficient, effective and robust optimization method. However, it needs a lot of computational time to find the optimal solution, especially when the objective function is complex. To overcome these difficulties, the concept of immunity based on vaccination is integrated into GA to promote the reproduction of excellent schemata. Furthermore, in order to improve the correctness of vaccines, based on the characteristic of GA and with the help of statistical concepts, how to peoduce the excellent group is proposed and vaccines are obtained from it. vaccine extraction, vaccine effectiveness determination for current generation are proposed. Experiments show that without compromising the solution quality, the proposed method reduces the computational time and increases the convergence rate greatly.
机译:遗传算法(GA)被广泛使用,因为它是一种高效,有效且鲁棒的优化方法。但是,要找到最佳解需要大量的计算时间,尤其是当目标函数很复杂时。为了克服这些困难,将基于疫苗接种的免疫概念整合到了GA中,以促进优秀图式的复制。此外,为了提高疫苗的正确性,基于遗传算法的特征并借助统计概念,提出了如何区分优秀群体并从中获得疫苗的方法。提出了疫苗提取,当代疫苗有效性的确定方法。实验表明,在不影响求解质量的前提下,该方法减少了计算时间,大大提高了收敛速度。

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