A Hybrid PSO-ACO Algorithm to Facilitate Software Project Scheduling

被引:0
作者
Joe, Praveen I. R. [1 ]
Malathy, E. M. [2 ]
Aishwarya, S. [3 ]
Akila, R. [4 ]
Akshaya, A. [5 ]
机构
[1] Vellore Inst Technol, Comp Sci & Engn, Chennai Campus, Chennai, Tamil Nadu, India
[2] Sri Sivasubramaniya Nadar Coll Engn, Informat Technol, Kalavakkam, India
[3] Zoho Corp Pvt Ltd, Chengalpattu, India
[4] CSS Corp Pvt Ltd, Nanakaramguda, India
[5] Anna Univ, Chennai, Tamil Nadu, India
关键词
Ant Colony Optimization; Particle Swarm Optimization; Software Project Scheduling; Swarm Intelligence; PARTICLE SWARM OPTIMIZATION;
D O I
10.4018/IJeC.304039
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
While tailoring software applications, in the present day scenario, there is a huge demand for cost-effective products; however, it is challenging for the developers to make a trade-off between cost and quality as well as between quality and time. Late delivery, sometimes, has become inevitable due to the reasons like improper time schedules, technical issues, changing customer requirements, miscommunication amongst team members, failure to analyse the risks involved, and underrating of resources like man cost, power, effort, etc. Here in this work an attempt has been made to study the advantages of swarm-based optimization techniques over traditional optimization approaches and thereby employ them efficiently to schedule projects. A hybrid PSO-ACO algorithm is proposed for scheduling purposes. The nuances of natural swarm cultures are appropriately incorporated into the software scheduling scenario, and the results are recorded and reported. It is observed that the readings are passible and are benchmarked through relevant measures of quality.
引用
收藏
页数:12
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