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引用次数: 1
摘要
进化算法比传统方法更能有效地求解方程的最优解。它还以分布式的方式以较少的费用快速求解大量参数大的方程。本文提出了一种新的分布式进化计算技术,将决策向量分解成更小的分量,并在短时间内得到最优解。在该技术中,提出了一种基于jacobi的时变自适应(JBTVA)混合进化算法。此外,还引入了一种新的选择方法——Best All selection (BAS)来选择最佳个体。实验结果表明,所提出的分布式系统对不同类型的大参数问题都能得到最优解,并形成了较好的加速。
A new distributed evolutionary computation technique for solving large number of equations
Evolutionary algorithm is more effective to gain optimal solution to solve equations than traditional methods. It also provides quick solution for solving large number of equations having huge parameters with less expense in distributed manner. This paper presents a new distributed evolutionary computation technique, which decomposes decision vectors into smaller components and achieves optimal solution in short time. In this technique, A Jacobi-based Time Variant Adaptive (JBTVA) Hybrid Evolutionary Algorithm is distributed. Moreover, a new selection method named Best All Selection (BAS) is introduced for selecting best individuals. Experimental results show that optimal solution is achieved for different kinds of problems having huge parameters and considerably speedup is formed in proposed distributed system.