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Decision support for project rescheduling to reduce software development delays based on ant colony optimization

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Version 2 2024-06-06, 03:18
Version 1 2018-05-17, 11:14
journal contribution
posted on 2018-01-01, 00:00 authored by W Zhang, Y Yang, Xiao LiuXiao Liu, C Zhang, X J Li, R B Xu, F Wang, M Ali Babar
Delays often occur during some activities in software development projects. Without handling of project delays effectively, many software development projects fail to meet their deadlines. If extra employees with same or similar skills and domain knowledge can be rescheduled for the remaining activities of the delayed projects, it can be possible to reduce or even eliminate existing delays in concurrent software development projects of similar nature. However, it is evident that employee rescheduling may result in delaying other activities, which may lead to
the problem of delay propagation. Hence, it is important to investigate how to reduce or even eliminate the delay in one project without impacting other projects. By nature this is an NP-hard problem. Therefore, we propose a novel generic rescheduling strategy based on adaptive ant colony optimization algorithm to provide decision support for software project managers to select appropriate employees to deal with project delays. We have carried out a set of comprehensive experiments to evaluate the performance of the proposed strategy. In addition, three real world software project instances are also utilized to evaluate our strategy. The results show that our strategy is effective,
efficient and able to outperform its representative counterparts significantly.

History

Journal

International Journal of Computational Intelligence Systems

Volume

11

Issue

1

Pagination

894 - 910

Publisher

Atlantis Press

Location

Paris, France

ISSN

1875-6883

eISSN

1875-6883

Language

eng

Publication classification

C Journal article; C1 Refereed article in a scholarly journal

Copyright notice

2018, The Authors