Airfreight forwarder's shipment planning: Shipment consolidation and containerization

This study focuses on an airfreight forwarder's shipment planning problem, while considering shipment consolidation and containerization in the international supply chain. Items belonging to different shipments from supplier's manufacturing warehouses are consolidated and loaded into Unit Loading Devices (ULDs) at outbound logistics hubs and to inbound logistics hubs by air transportation, where items are unloaded from the ULDs and distributed to the corresponding retailers by parcel delivery. A three-dimensional multiple bin size bin packing problem is considered, where items are consolidated and orthogonally loaded into ULDs of heterogeneous irregular shapes, where each item has a required latest allowable delivery time. A mixed integer programming model is formulated for the problem, which aims to determine the optimal route planning and feasible packing scheme for the transported items. This study develops a biased random-key genetic algorithm combining a threedimensional bin packing heuristic to solve the problem. A two-phase greedy heuristic with a chaotic system is designed for the generation of initial population. Additionally, a catastrophe operator and a self-adaptive neighborhood search are put forward to further improve the performance of the algorithm. A numerical experiment is given to demonstrate the feasibility of formulation and effectiveness of algorithm by comparing with ILOG CPLEX, and managerial insights are provided.