Abstract
PurposeThis paper studies the location-inventory problem (LIP) in pallet pooling systems to improve resource utilization and save logistics costs, which is a new extension of the classical LIP and also an application of the LIP in pallet pooling systems.Design/methodology/approachA mixed-integer linear programming is established, considering the location problem of pallet pooling centers (PPCs) with multi-level capacity, multi-period inventory management and bi-directional logistics. Owing to the computational complexity of the problem, a hybrid genetic algorithm (GA) is then proposed, where three local searching strategies are designed to improve the problem-solving efficiency. Lastly, numerical experiments are carried out to validate the feasibility of the established model and the efficiency of the proposed algorithm.FindingsThe results of numerical experiments show that (1) the proposed model can obtain the integrated optimal solution of the location problem and inventory management, which is better than the two-stage model and the model with single-level capacity; (2) the total cost and network structure are sensitive to the number of PPCs, the unit inventory cost, the proportion of repairable pallets and the fixed transportation cost and (3) the proposed hybrid GA shows good performance in terms of solution quality and computational time.Originality/valueThe established model extends the classical LIP by considering more practical factors, and the proposed algorithm provides support for solving large-scale problems. In addition, this study can also offer valuable decision support for managers in pallet pooling systems.