Adaptive hybrid optimization for integrated project scheduling and staffing problem with time/resource trade-offs
The integration of project scheduling and human resource allocation is crucial in modern project management, particularly in complex and resource-constrained environments. This study addresses the Integrated Project Scheduling and Personnel Staffing Problem (IPSPSP) with time/resource trade-offs by...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-12-01
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| Series: | Operations Research Perspectives |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214716025000223 |
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| Summary: | The integration of project scheduling and human resource allocation is crucial in modern project management, particularly in complex and resource-constrained environments. This study addresses the Integrated Project Scheduling and Personnel Staffing Problem (IPSPSP) with time/resource trade-offs by proposing a dual-objective optimization model that minimizes both project duration and personnel cost. To solve this problem, we introduce an adaptive hybrid algorithm combining the Non-dominated Sorting Genetic Algorithm II (NSGA-II) and Multi-Objective Particle Swarm Optimization (MOPSO). The algorithm employs hybrid encoding for activity modes, activity priority lists and personnel allocation plans, coupled with a hypervolume-based adaptive search mechanism to improve solution quality. Experimental results demonstrate that the adaptive hybrid algorithm outperforms standalone NSGA-II and MOPSO in generating schedules and optimizing resource allocation. This study makes significant contributions by presenting a novel integrated model tailored for projects, an effective adaptive hybrid optimization algorithm and a comprehensive performance evaluation, thereby advancing the field of integrated scheduling and staffing in project management. |
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| ISSN: | 2214-7160 |