A Hybrid PSO-ACO Algorithm to Facilitate Software Project Scheduling

• Published in: International journal of e-collaboration Vol. 18; no. 2; pp. 1 - 12
• Main Authors: Praveen Joe I. R, Malathy E. M, Aishwarya S, Akila R, Akshaya A
• Format: Journal Article
• Language: English
• Published: Hershey IGI Global 01.01.2022
• Subjects: Algorithms; Ant colony optimization; Applications programs; Backup software; Cost analysis; Mathematical optimization; Optimization techniques; Schedules; Scheduling; Software; Technology application
• ISSN: 1548-3673; 1548-3681
• DOI: 10.4018/IJeC.304039

While tailoring software applications, in the present day scenario, there is a huge demand for cost effective products however it is so challenging for the developers on how 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 in to the software scheduling scenario and the results are recorded and reported. It is observed that the readings are passible and are bench marked through relevant measures of quality.