A Model-Based Hybrid System for Human Resource Allocation in Multi-Project Management

Abstract

Multi-project management (MPM) effectively handles project-based organizations that use multi-skilled shared resources to execute projects, which is crucial for engineering teamwork and transdisciplinary research. Hence, allocating appropriate resources to projects is a significant challenge. Furthermore, projects are often executed in dynamic contexts with various sources of uncertainty, necessitating resource reallocation and rescheduling, which might influence other projects due to interdependencies. While mathematical approaches can help with low complexity problems or in a relatively static environment, they have limitations in characterizing interrelationships in multi-project settings and adapting to dynamic change. Considering these problems, we propose a model-based hybrid simulation system comprising system dynamics (SD) and agent-based simulation (ABS). SD can refine the complexity of uncertainty, while ABS provides decision-making support for dynamic changes. ABS models both projects and resources as agents, whereas SD reproduces the cause-and-effect relationship between project activities. Projects require resources to accomplish their scheduled work, while resources provide their skills and staffing. The outcome helps get insights into the impact of dynamic changes on allocation to the project execution process. The system is used as a decision-support tool for evaluating and obtaining feasible resource allocation solutions considering dependencies, uncertain occurrences, and resource constraints. Another intention is to motivate a transdisciplinary-enabling framework to support the systematic integration of knowledge with stakeholders.