Application of Machine Learning Methods for Pallet Loading Problem

Batin Latif Aylak,Bashir Salah,Okan Oral,Manjeet Singh,Murat İnce,Gürsel Süer,Najat Almasarwah

doi:10.3390/app11188304

Abstract

Because of continuous competition in the corporate industrial sector, numerous companies are always looking for strategies to ensure timely product delivery to survive against their competitors. For this reason, logistics play a significant role in the warehousing, shipments, and transportation of the products. Therefore, the high utilization of resources can improve the profit margins and reduce unnecessary storage or shipping costs. One significant issue in shipments is the Pallet Loading Problem (PLP) which can generally be solved by seeking to maximize the total number of boxes to be loaded on a pallet. In many previous studies, various solutions for the PLP have been suggested in the context of logistics and shipment delivery systems. In this paper, a novel two-phase approach is presented by utilizing a number of Machine Learning (ML) models to tackle the PLP. The dataset utilized in this study was obtained from the DHL supply chain system. According to the training and testing of various ML models, our results show that a very high (>85%) Pallet Utilization Volume (PUV) was obtained, and an accuracy of >89% was determined to predict an accurate loading arrangement of boxes on a suitable pallet. Furthermore, a comprehensive analysis of all the results on the basis of a comparison of several ML models is provided in order to show the efficacy of the proposed methodology.

Highlights

Because of the advancements in transportation technology, a large number of products are shipped to the customers globally using a wide variety of transport vehicles such as trucks, planes, ships, etc., on a daily basis
In our previous study [10], 15 real-life datasets were obtained from the DHL supply chain, and the proposed algorithm was applied to this dataset
This paper shows an application of Machine Learning (ML) methods in a warehouse for the Pallets Loading Problem (PLP)

Summary

Introduction

Because of the advancements in transportation technology, a large number of products are shipped to the customers globally using a wide variety of transport vehicles such as trucks, planes, ships, etc., on a daily basis. These products are first packed in boxes and placed on pallets and loaded into trucks, containers, and other transportation options [1]. This whole process necessitates optimizing the smallest volume of the utilization of resources at each step in a cost-effective manner. It is quite evident that efficient utilization of pallets may entail the reduction of goods traffic, thereby preserving the company’s time, resources, and the involved costs.

Objectives

Methods

Results

Conclusion