Evolutionary Algorithm for Software Project Scheduling Considering Team Relationships

Human relationships have a great impact on the software development process. Meanwhile, project development may require the acquisition of new skills that employees have not yet acquired due to changes in customer requirements. However, such factors are seldom incorporated into software project scheduling problem. To address this, a novel mathematical model considering the team relationships is established for software project scheduling problem. This model introduces the communication cost factor of each employee, and analyses its quantitative connections with changes in human relationships and the growth of skill proficiency respectively. In addition, a selection mechanism for external employees is designed to meet new skill requirements. To solve the model, an improved bi-population discrete evolutionary algorithm based on information feedback is proposed. The heuristic information of “employee suitability” is utilized in initialization to obtain better initial individuals. The feedback mechanism based on “evolutionary quality” is applied to provide an effective strategy for adaptive tuning of subpopulation size. The selection probabilities of distinct crossover operators are adjusted according to the “improved quantity” to increase crossover efficiency. Moreover, an enhanced local search strategy based on the “degree of team cooperation” and the “improved quantity” is developed. Experimental results show that by considering human relationships under different communication cost factors, the duration and cost of the project are significantly reduced. Compared with four state-of-the-art algorithms, the scheduling performance of the proposed algorithm can be improved by 10.6374% to 25.8566%.