Multi-Project Staff Scheduling Optimization Considering Employee Welfare in Construction Projects

Abstract

Multi-project staff scheduling optimization is a critical challenge in engineering management. However, traditional methods often overlook employee welfare, resulting in scheduling solutions that lack a people-centered approach. This study develops a multi-objective model that incorporates employee welfare to balance project performance and staff well-being. A mixed-integer programming model is proposed, integrating task allocation, resource scheduling, income growth, and workload balance as core optimization objectives. An improved Spider Wasp Optimization Algorithm (SWOIM) is employed to solve this model. The experimental results demonstrate that SWOIM outperforms conventional optimization algorithms in convergence speed, stability, and solution quality. It enhances staff scheduling efficiency while ensuring fair compensation and balanced workload distribution. A case study further validates the practical applicability of the proposed approach, showing that the optimized schedule not only improves task allocation but also enhances employee satisfaction and overall organizational performance. This study presents a people-centered scheduling framework aligned with sustainable workforce management principles and offers practical insights for improving multi-project coordination.