The purpose of this research is to reduce the workload on the project manager by improving the efficiency of scheduling work in IT project management. In general, the delivery time and cost of the project are in a trade-off relationship, and the priority varies depending on the environment and circumstances. Therefore, in this research, we propose the software which generates schedules automatically using multi-objective genetic algorithm to minimize the objective functions of (1) the delivery time, (2) the number of days in duplicate task for all members and (3) the number of members. While there are many prior studies on project scheduling method using metaheuristics, in this research, we focus on objective functions and constraints specific to IT project scheduling. In the model of this study, we show that part of the Pareto front can be obtained as an exact solution with a small computational complexity, and search efficiency can be improved by incorporating them into the initial population. The project manager can select a schedule suitable for the situation of the project from semi-optimal solutions generated by the proposed software. The proposed software generates the schedule in realistic time using a general PC. The results of numerical experiments and interviews show that the proposed software is effective for reducing the workload of the project manager.