A novel multi-level quantization scheme for discrete particle swarm optimization

Hwachang Song, Ryan B. Diolata, Y. Joo
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引用次数: 3

Abstract

This paper presents a novel multi-level quantization scheme which best approximates the sigmoid function for multi-value discrete variable transformation in PSO. We define the set of multi-level quantization as integer multiples of powers-of-two terms to efficiently approximate the sigmoid function in transforming particle's position into multilevel discrete values. In this paper, the feasibility of the proposed technique was tested in photovoltaic (PV) system allocation problem, and a comparison study with genetic algorithm (GA) is performed to show the quality of the solutions obtained.
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一种新的离散粒子群优化多级量化方案
针对PSO中多值离散变量变换,提出了一种最接近sigmoid函数的多层次量化方案。为了有效地逼近将粒子位置转化为多级离散值的sigmoid函数,我们将多级量化集合定义为2次幂的整数倍。本文以光伏系统分配问题为例,验证了该方法的可行性,并与遗传算法(GA)进行了比较研究,以证明所得到的解的质量。
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