Data-Driven Predictive Modelling for Last Mile Delivery

Yew, Ze Xuan (2024) Data-Driven Predictive Modelling for Last Mile Delivery. Final Year Project (Bachelor), Tunku Abdul Rahman University of Management and Technology.

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Abstract

This study focuses on the critical aspect of modern logistics: last-mile delivery, which has gained significance due to the convenience of online purchasing in this era. Data from 2016-2018 will be examined, estimating daily order quantity through time series analysis. There are five chapters in the report. Chapter 1 introduces the project's significance, outlining its objectives and scope within the supply chain industry. Chapter 2 reviews recent literature on predictive modelling and last-mile delivery, identifying trends and research gaps. Chapter 3 explains the methodology, detailing the selection and evaluation of four predictive models for last-mile delivery optimization. The accuracy of models is ensured by model diagnostic techniques. Chapter 4 discusses findings from predictive modelling efforts, including model performance evaluation, order forecasting, and historical allocation analysis. In Chapter 5, key insights and implications of the research are summarized. Future research avenues are proposed to enhance last-mile delivery efficiency. This study aims to contribute to the ongoing discourse on logistics optimisation, particularly in improving the efficiency of the final leg of delivery journeys. Keywords: forecasting, last mile delivery, time series, supply chain.