Integrated capacity planning and multi-project scheduling considering resource transfer and idleness
针对客户驱动生产系统，提出一个双层框架，在战术层进行资源分配并考虑转移成本，在运营层进行详细调度，通过自适应大邻域搜索算法实现总成本最小化，适用于按订单设计和按订单生产环境。
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.