Dataset

Reducing costs and improving efficiency in logistics distribution centres (LDCs) have become critical objectives for logistics companies. The allocation of equipment and personnel is central to achieving these objectives within existing facilities. However, few existing solutions effectively address the collaborative optimisation of both equipment and personnel allocations. This study investigates the collaborative optimisation of equipment and personnel allocations in LDCs by establishing a two-stage model for equipment and personnel allocation. A genetic algorithm (GA) was employed to solve the proposed models, yielding a cost-minimised allocation scheme under known operational workloads. Finally, a computational case study was conducted using actual survey data from an LDC in Beijing. Compared to the original scheme, the optimised allocation scheme reduces equipment and personnel costs by 21.4% and 7.0%, respectively. Sensitivity analysis of equipment utilisation provides recommendations for the equipment allocation section of the model. The computational experiment also demonstrated the effectiveness of the genetic algorithm by comparing it with PSO and ACO.