最小化网络编码资源:一种改进的粒子群优化方法

Huanlai Xing, Fuhong Song, Zhaoyuan Wang, Tianrui Li, Yan Yang
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引用次数: 1

摘要

本文研究了如何有效地减少网络编码资源的问题。提出了一种改进的粒子群优化算法(PSO)来解决这一问题,并将路径链接(PR)的概念融入到进化框架中。PR是一种高效的局部搜索启发式算法,它利用了特定于问题的领域知识,有助于在进化搜索的全局探索和局部开发之间取得更好的平衡。仿真结果表明,该算法在求解质量、收敛性和计算时间等方面优于现有和常用的进化算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On Minimizing Network Coding Resource: A Modified Particle Swarm Optimization Approach
This paper studies the problem of how to efficiently minimize network coding resource. A modified particle swarm optimization (PSO) algorithm is proposed to tackle the problem, with the concept of path-relinking (PR) integrated into the evolutionary framework. As an efficient local search heuristic that makes use of problem-specific domain knowledge, PR helps strike a better balance between global exploration and local exploitation for the evolutionary search. Simulation results demonstrate that the proposed algorithm overweighs a number of existing and commonly used evolutionary algorithms (EAs) in terms of the solution quality, convergence, and computational time.
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