粒子能量优化解的独特计算方法

N. Akhter, Laraib Asghar, Sobia Arbab, F. Batool
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引用次数: 0

摘要

“汤姆逊问题”用于确定球面上电子的最小能量构型。我们将这一困难转化为优化问题,并借助粒子群优化(PSO)和量子粒子群优化(QPSO)等智能计算技术来解决这一问题。为了提高系统的全局搜索能力,设计了量子粒子群优化算法。根据仿真数据,对汤姆逊问题进行了研究和评价,并且需要控制的参数更少。在这项工作中,我们将结果与遗传算法和粒子群算法进行了比较,发现量子粒子群算法在提供接近最优的结果方面非常有效和成功。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Distinctive Computational Approaches for Solution of Energy Optimization of Particles
The “Thomson problem’ is used to determine the minimum energy configuration of electrons on the sphere’ s surface. We turned this difficulty into an optimization problem, which we addressed with the help of intelligent computational techniques like Particle Swarm Optimization (PSO) and Quantum Particle Swarm Optimization (QPSO). To enhance the system’s global searching ability, a Quantum behaved Particle Swarm Optimization algorithm is designed. The Thomson’s problem is investigated and appraised, and has fewer parameters to govern, according to simulation data. In this work QPSO is extremely effective and successful at delivering near- optimal results, as we compared the results with Genetic Algorithm and PSO.
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