A novel hierarchical approach for a heterogeneous 3D pallet loading problem subject to factual loading and delivery constraints

Abstract

This paper presents a hierarchical approach, which consists of a two-stage genetic algorithm and a mixed integer linear programming, for a heterogeneous three-dimensional pallet loading problem in consideration of the rotation, the relative positioning, the load-bearing strength and the fragility constraints. Stage #1 of the proposed two-stage genetic algorithm provides to reduce the number of items to be packed by combining similar items based on a stack-building approach. And, stage #2 provides to estimate the number of required free pallets. After that, the proposed mixed integer linear programming solves the problem considering the findings of the proposed two-stage genetic algorithm. The proposed hierarchical approach was tested on well-known instances leading to favourable results and compared with a decent solution approach. In addition, a case study was presented.