Solving Pallet loading Problem with Real-World Constraints

TL;DR

This paper introduces a branch and bound algorithm for the pallet loading problem that incorporates real-world constraints like stability and inertial forces, improving efficiency in logistics operations.

Contribution

It presents a novel branch and bound method that considers real-world constraints and heuristically reduces search space for NP-hard pallet loading problems.

Findings

Algorithm improves computational efficiency

Ensures pallet stability under real-world conditions

Addresses NP-hardness with heuristic subset selection

Abstract

Efficient cargo packing and transport unit stacking play a vital role in enhancing logistics efficiency and reducing costs in the field of logistics. This article focuses on the challenging problem of loading transport units onto pallets, which belongs to the class of NP-hard problems. We propose a novel method for solving the pallet loading problem using a branch and bound algorithm, where there is a loading order of transport units. The derived algorithm considers only a heuristically favourable subset of possible positions of the transport units, which has a positive effect on computability. Furthermore, it is ensured that the pallet configuration meets real-world constraints, such as the stability of the position of transport units under the influence of transport inertial forces and gravity.