Integrated capacity planning and multi-project scheduling considering resource transfer and idleness
Hu, Xuejun Wang, Yuhao Zhou, Zhongbao Wang, Jianjiang
Hu, Xuejun
Wang, Yuhao
Zhou, Zhongbao
Wang, Jianjiang
Publication Type
Journal article with impact factor
Editor
Supervisor
Publication Year
2026-05-03
Journal
International Journal of Production Research
Book
Publication Volume
64
Publication Issue
9
Publication Begin page
1
Publication End page
24
Publication Number of pages
Collections
Abstract
This paper develops a dual-level framework addressing resource allocation and scheduling challenges in customer-driven production systems involving multi-mode projects with predefined release/due dates. At the tactical level, global resources undergo time-dependent allocation across projects, with transfer costs incurred during dynamic redistribution. Operational-level scheduling utilises these allocations for detailed sub-project execution. The objective minimises total costs encompassing transfer, idle, and indirect expenses. To streamline resource transfers, we introduce a novel ‘blocking’ strategy that partitions time-varying allocations into distinct ‘resource blocks’. We propose an adaptive large neighbourhood search (ALNS) and genetic algorithm (GA) featuring a ‘project macro-mode – activity sequence – activity mode’ hybrid encoding that integrates operational objectives within the tactical framework. Numerical studies confirm the superiority of ALNS, demonstrating it achieves 92% faster computation than CPLEX on small-scale instances while maintaining only a 0.47% optimality gap, reduces costs by up to 13.2% versus GA across 80 test instances, and shows particularly high efficacy in resource-constrained scenarios. The framework demonstrates significant potential for application in complex manufacturing environments like engineer-to-order and make-to-order production, directly contributing to reduced lead times, lower costs, and improved system throughput. Sensitivity analysis provides actionable insights on cost-drivers for production and project management practitioners.
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Organizational Units
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Keywords
4014 Manufacturing Engineering, 40 Engineering