Modeling Human Resource Experience Evolution for Multiobjective Project Scheduling in Large Scale Software Projects

The software project scheduling (SPS) is a project-scheduling problem where limited human resources are assigned to the tasks in multi-team settings. Besides other dynamic events, employees experience evolution has direct influence completing large-scale projects within budget and time. In this paper, new SPS model developed as multi-objective optimization problem, which incorporates with their learning ability over experimental results on 24 instances (including six real-world instances) show that reduces duration by 40% while being budget. provide evidence consideration of reallocation under events significantly optimizes schedules. Moreover, evaluated state-of-the-art algorithms bi-criterion (BCE), NSGA-II, NSGA-III, Two_Arch2, OMOPSO, speed-constrained particle swarm (SMPSO) BCE demonstrated distinct superiority for 63% data instances.