Efficient robust project schedule method based on iterated local search with high-speed simulations

Abstract

Project schedule management, which involves generating and revising a schedule, is a critical decision-making process in uncertain environments. However, methods that can be used in project schedule management, particularly for large and complex projects, have so far been insufficiently studied. We believe that addressing this issue is essential to enable this process to be successfully adapted to practical projects. This study proposes a scheduling method that can generate a robust schedule insensitive to delays. The proposed method accurately evaluates schedule robustness using simulations, even for complex projects involving multiple decisions. As the simulation element of this process can be time-consuming, particularly for large-scale project instances, it is necessary to accelerate the evaluation process and ensure the search is performed efficiently. The proposed method reduces the computational time required for the evaluation process by employing parallel processing on a graphics processing unit (GPU) and utilizing simple simulations. To search for various solutions efficiently, the kick operation was developed that is specifically tailored to address the target problem. Numerical experiments confirmed the fundamental properties of the proposed method and demonstrated its effectiveness in comparison with previously employed methods in this area.

Keywords

• project scheduling
• uncertainty
• simulation-based evaluation
• graphics processing unit-accelerated computing
• iterated local search