Conflict-Free scheduling of interconnected reclaimers in dry bulk terminals

Coordinating multiple reclaimers for conflict-free route planning across parallel tracks is essential in dry bulk terminal operations. Currently, however, reclaimer scheduling is limited to single-track scenarios without integrated task assignment, which constrains overall handling capacity. To overcome this limitation, this paper employs a time-space network (TSN) model to represent reclaiming operations, incorporating sequencing, task assignment, and non-crossing constraints. The model thereby captures the full complexity of stockyard operations. The reclaiming route planning problem is formulated as a mixed-integer programming (MIP) model, which is computationally intractable. To improve computational efficiency, we propose an innovative two-level metaheuristic framework that separates task sequences from conflict-free route generation, simplifies the encoding process, accelerates the search procedure, and prevents the creation of infeasible solutions. Building on this two-level framework, we develop a centralized two-level metaheuristic algorithm (CTLM) and a parallel two-level metaheuristic algorithm (PTLM). Comprehensive computational experiments show that the proposed CTLM significantly outperforms the Gurobi solver and three commonly used methods regarding solution quality. PTLM achieves an average speedup ratio of 4.07 in large-scale instances with only a very small degree of accuracy loss, making it more suitable for practical terminal operations.