Evolutionary Algorithm for Software Project Scheduling Considering Team Relationships

Abstract

During software development, human relationships between team members have a significiant influence on development efficiency. Meanwhile, finishing tasks might require new skills that employees have not yet grasped due to changes of customer requirements or other reasons. However, such factors have not been taken seriously in existing software project scheduling work. To address this, a software project scheduling model considering the team relationships is established, which minimizes the duration and cost of software projects by finding the best employee-task allocation. The model introduces the communication cost factor of each team member, and its quantitative connections with changes in human relationships and the growth of skill proficiency are analyzed, respectively. In addition, a selection mechanism for external employees is designed to meet new skill requirements. To solve the model, a bi-population discrete evolutionary algorithm based on information feedback is proposed. Some initial individuals are generated by utilizing heuristic information of "employee suitability". Adaptive tuning of the subpopulation size is realized by the feedback of "evolutionary quality". The selection probabilities of different crossover operators are adjusted according to the "improvement rate". Additionally, a local search strategy is developed based on the "degree of team cooperation" and the ‘improvement rate’. The experimental results show that by considering human relationships under different communication cost factors, the scheduling performance is significantly improved. Compared with the state-of-the-art algorithms, the proposed algorithm can obtain a schedule with a higher quality in problems of different scales.