Software Project Scheduling Using Ant Colony and Artificial Bee Colony Algorithm

The success rate of software projects is still not at the desired level despite of the technological advances. The vast majority of software projects can not be delivered at the desired specifications or can be delivered beyond the planned budget and time. The software project schedule is one of the important factors that influence this success. Due to it includes parameters such as human resource, time, cost, and process sequence of activities, state space is too big for software project scheduling. So it is difficult to create a software project schedule for software project managers. In this study, using human resource and activities these resource can do, it is tried to obtain minimum project completion time while creating software project schedule using ant colony and artificial bee colony optimization algorithm and results are analyzed. According the results obtained, both methods are successful in software project scheduling. Although the processing time of the artificial bee colony algorithm is slower than ant colony optimization algorithm, it has been determined that when the number of colony / food source is increased, it is converged to minimum project completion time faster than the ant colony algorithm