Abstract
In smart logistics and transportation, packages are usually packed and loaded onto pallets, and then loaded into containers for transportation. Robotic arms are used for palletising operations in highly automated industry chains. These must be real-time and the loaded pallets are stable. Thus, an optimal or near-optimal solution to Pallet Loading Problems (PLP) can help such complex logistic operations, e.g., warehouse management, shipping, and airline cargo transportation, to achieve high efficiency and low cost. This survey paper discusses different PLP scenarios and indicates their various constraints and objectives. Then, we summarise different algorithms and show their advantages and disadvantages when solving PLP. Another contribution is to discuss the future research directions to advance this research field.
| Original language | English (US) |
|---|---|
| Journal | International Journal of Production Research |
| DOIs | |
| State | Accepted/In press - 2025 |
All Science Journal Classification (ASJC) codes
- Strategy and Management
- Management Science and Operations Research
- Industrial and Manufacturing Engineering
Keywords
- 3D bin packing problem
- container loading problem
- convolutional neural network
- intelligent optimisation
- Pallet loading problem
- reinforcement learning