Cloud workflow scheduling algorithm based on multi-objective hybrid particle swarm optimisation

被引：3
|
作者：
Dai, Gang [1 ,2 ]
Xu, Baomin [1 ]
Peng, Jianfeng [3 ]
Zhang, Lei [4 ]
机构：
[1] Beijing Jiaotong Univ, Sch Comp & Informat Technol, Beijing, Peoples R China
[2] China Univ Petr Beijing KARAMAY, Karamay City, Xinjiang, Peoples R China
[3] China Railway Informat Engn Grp Co Ltd SINORAIL, Beijing, Peoples R China
[4] Beijing Jiaotong Univ, Haibin Coll, Sch Comp Sci, Huanghua, Hebei, Peoples R China
来源：
INTERNATIONAL JOURNAL OF GRID AND UTILITY COMPUTING | 2021年 / 12卷 / 03期
关键词：
hill climbing algorithm; task scheduling; particle swarm optimisation; cloud workflow;
D O I：
10.1504/IJGUC.2021.117850
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Particle swarm optimisation has been widely used in solving scheduling problems. This paper proposes a hybrid algorithm namely Hill Climbing with Multi-objective Particle Swarm Optimisation called HCMOPSO, which is based on heuristic local search and multi-objective particle swarm optimisation algorithm. HCMOPSO introduces hill climbing optimisation techniques into particle swarm optimisation algorithm to improve the local search ability. Experimental results show that the HCMOPSO is an effective cloud workflow scheduling algorithm, which has faster convergence velocity and better optimisation ability.
引用
收藏
页码：287 / 301
页数：15
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