具有确定性和离散动力学的基于种群的优化

Yuya Kurita, T. Tsubone
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引用次数: 0

摘要

本文提出了一种基于分段常数振荡器(ipos - pco)的基于群体优化的方法单元整数算法。众所周知的粒子群优化方法(PSO)有几个开放性问题。我们关注其中的两个。首先,为了解决离散优化问题,粒子群算法需要进行一些修改。其次,由于粒子群动力学中存在随机因素,对其动力学行为的分析相当复杂。在以往的工作中,提出了一些解决问题的方法。然而,没有一种方法可以同时解决这两个问题。然后,本文考虑了一种确定性的离散方法。我们将所提出的方法与一种重新定位到格点附近的离散粒子群算法进行了比较,验证了所提出方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Population-based optimization having deterministic and discrete dynamics
In this paper, we propose a method celled Integer algorithm of Population-based Optimization based on Piecewise Constant Oscillator (IPO-PCO). Well known Particle Swarm Optimization method (PSO) has several open problems. We focus on two of them. First, in order to solve discrete optimization problems, PSO needs some modifications. Second, since PSO has stochastic factors in the dynamics, the analysis of the dynamic behavior is pretty complex. Some means to resolve the problems have been proposed in previous works. However there is no method which can manage both problems. Then, this paper considers a deterministic and discrete method. We compare the proposed method with a discretized PSO by repositioned to near lattice point and verify the effectiveness of the propose method.
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