Ant colony algorithm based scheduling for handling software project delay
Version 2 2024-06-04, 06:37Version 2 2024-06-04, 06:37
Version 1 2017-07-06, 15:07Version 1 2017-07-06, 15:07
conference contribution
posted on 2024-06-04, 06:37authored byW Zhang, Y Yang, J Xiao, Xiao LiuXiao Liu, MA Babar
Delay on a critical path may cause the failure in meeting the software project deadline. By adding extra employees with similar skills for help, the delay is expected to be eliminated or reduced. However, the originally scheduled activities may be suspended due to reallocation of employees, which may lead to the problem of delay propagation. So how to minimize and even eliminate the delay without delay propagation is worth investigation. In this paper, we first use a simple scenario to demonstrate the problem of employee scheduling which shows that in the scheduling process, one activity can have many ways for selecting employees from another project. In fact, the searching path in a multi-branch tree and its complete traversal is a NP hard problem. Furthermore when the scale of the problem becomes large, it is impractical to generate a search tree for implementation. Therefore, we propose an ant colony algorithm to address such a problem. Both case studies and initial simulation results demonstrate that our proposed algorithm can obtain feasible solutions under different circumstances.