Space Splitting and Merging Technique for Online 3-D Bin Packing
Thanh-Hung Nguyen, Xuan‐Thuan Nguyen
Abstract
This paper introduces a novel method for online 3-D bin packing, which is a strongly NP-hard problem, based on a space splitting and merging technique. In this scenario, the incoming box is unknown and must be immediately packed. The problem has many applications in industries that use manipulators to automate the packing process. The main idea of the approach is to divide the bin into spaces. These spaces are then categorized into one of two types of data structures: main and secondary data structures. Each node in the main data structure holds the information of a space that can be used to fit a new box. Each node in the secondary data structure holds the information of a space that cannot be used to place a box. The search algorithm based on these two data structures reduces the required search effort and simplifies the organizing and editing of the data structure. The experimental results demonstrate that the proposed method can achieve a packed volume ratio of up to 83% in the case of multiple bins being used. The position of a placed box can be found within milliseconds.