Solving software project scheduling problems with ant colony optimization

2013 ◽  
Vol 40 (1) ◽  
pp. 33-46 ◽  
Author(s):  
Jing Xiao ◽  
Xian-Ting Ao ◽  
Yong Tang
Keyword(s):  
Ant Colony Optimization ◽  
Project Scheduling ◽  
Ant Colony ◽  
Software Project ◽  
Scheduling Problems

scholarly journals Retraction: Ant colony optimization and event-based dynamic task scheduling and staffing for software projects (IOP Conf. Ser.: Mater. Sci. Eng. 263 042029)

2017 ◽  
Vol 263 (4) ◽  
pp. 042159
Keyword(s):  
Ant Colony Optimization ◽  
Project Scheduling ◽  
Computer Applications ◽  
Ant Colony ◽  
Software Project ◽  
Software Projects ◽  
Project Management System ◽  
Dynamic Task ◽  
Event Based ◽  
Dynamic Task Scheduling

This article has been retracted by IOP Publishing following an allegation that this article contains text overlap from multiple unreferenced sources [1, 2]. IOP Publishing has investigated and agree the article constitutes plagiarism. IOP Publishing also expresses concern regarding a number of nonsensical phrases used in the article, which suggests the article may have been created at least partly by artificial intelligence or translation software. Vijyan Ellappan agrees to this retraction. J Ashwini has not responded to our enquiries. 1. W. Chen and J. Zhang, "Ant Colony Optimization for Software Project Scheduling and Staffing with an Event-Based Scheduler," in IEEE Transactions on Software Engineering, vol. 39, no. 1, pp. 1-17, Jan. 2013, doi: 10.1109/TSE.2012.17 2. R. S. Vairagade et al, "Survey on Project Management System using Event based Scheduler and Ant Colony Optimization" International Journal of Computer Applications, Volume 133 - No.17, January 2016, doi: 10.5120/ijca2016907948 Retraction published: 11 November 2021

Penerapan Algoritma ACO untuk Penjadwalan Kuliah Pengganti pada Perguruan Tinggi (Studi Kasus: Program Studi Informatika, Universitas Multimedia Nusantara)

2019 ◽  
Vol 9 (2) ◽  
pp. 79-85
Author(s):  
Indah Noviasari ◽  
Andre Rusli ◽  
Seng Hansun
Keyword(s):  
Ant Colony Optimization ◽  
Educational Institution ◽  
Ease Of Use ◽  
Perceived Usefulness ◽  
Ant Colony ◽  
Scheduling Problems ◽  
Perceived Ease Of Use ◽  
Ant Colony Optimization Algorithm ◽  
Scheduling System ◽  
Course Scheduling

Students and scheduling are both essential parts in a higher educational institution. However, after schedules are arranged and students has agreed to them, there are some occasions that can occur beyond the control of the university or lecturer which require the courses to be cancelled and arranged for replacement course schedules. At Universitas Multimedia Nusantara, an agreement between lecturers and students manually every time to establish a replacement course. The agreement consists of a replacement date and time that will be registered to the division of BAAK UMN which then enter the new schedule to the system. In this study, Ant Colony Optimization algorithm is implemented for scheduling replacement courses to make it easier and less time consuming. The Ant Colony Optimization (ACO) algorithm is chosen because it is proven to be effective when implemented to many scheduling problems. Result shows that ACO could enhance the scheduling system in Universitas Multimedia Nusantara, which specifically tested on the Department of Informatics replacement course scheduling system. Furthermore, the newly built system has also been tested by several lecturers of Informatics UMN with a good level of perceived usefulness and perceived ease of use. Keywords—scheduling system, replacement course, Universitas Multimedia Nusantara, Ant Colony Optimization

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