Essays on Scheduling Problems in Emerging Logistics Operations

Abstract

In recent years we have witnessed the fast development of emerging technologies in the logistics industry, from warehousing to transportation. These technologies call for new operational models to fully unlock their potentials. This thesis focuses on two scheduling problems that are incurred in such situations.

The first problem is the scheduling of battery swapping and charging for electric buses. Battery charging is a key factor in the performance of electric vehicles. Generally speaking, there are two approaches, direct charging by plug-in, and battery swapping, each with its pros and pons. Battery swapping is particularly suitable for electric buses given that the electricity consumption of buses is regular with high certainty. In this thesis we consider a situation where a bus company does battery swapping for multiple bus lines at one central station. The scheduling problem is incurred by the time-varying electricity price. We present a network flow model to formulate the problem. Computational experiments demonstrate a cost saving ranging from 10% to 30% when compared to the intuitive alternative methods.

The second problem is retrieval scheduling in an automatic warehouse. Specifically, we consider a puzzle-based storage (PBS) system with block movement and simultaneous movement. Block movement refers that multiple items in one line can move together, and simultaneous movement refers that block movements occur simultaneously. For the static problem of retrieving multiple items, we explore the required number of escorts to move them using the minimum retrieval time, especially for a combine item (a product occupies multiple cells). It indicates that the optimal moving schedule is to move escorts (empty cells) into different rows and columns. For the dynamic retrieval problem where multiple orders arrive randomly over time, we apply the rolling-horizon strategy. Numerical experiments reveal that the retrieval time is near-optimal for PBS in a dynamic scene.

Date of Award	2025
Original language	English
Awarding Institution	The Hong Kong University of Science and Technology
Supervisor	Xiangtong QI (Supervisor)