文章基本信息

标题：Parallel Whale Optimization Algorithm for Maximum Flow Problem
本地全文：下载
作者：Raja Masadeh ; Abdullah Alzaqebah ; Bushra Smadi 等
期刊名称：Modern Applied Science
印刷版ISSN：1913-1844
电子版ISSN：1913-1852
出版年度：2020
卷号：14
期号：3
页码：30-44
DOI：10.5539/mas.v14n3p30
语种：English
出版社：Canadian Center of Science and Education
摘要：Maximum Flow Problem (MFP) is considered as one of several famous problems in directed graphs. Many researchers studied MFP and its applications to solve problems using different techniques. One of the most popular algorithms that are employed to solve MFP is Ford-Fulkerson algorithm. However, this algorithm has long run time when it comes to application with large data size. For this reason, this study presents a parallel whale optimization (PWO) algorithm to get maximum flow in a weighted directed graph. The PWO algorithm is implemented and tested on datasets with different sizes. The PWO algorithm achieved up to 3.79 speedup on a machine with 4 processors.