Author Description

This dissertation, "Mathematical Modeling for Warehouse Logistics: Stock Loading and Order Picking" by Li, Pan,, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: Logistics makes extensive use of human and material resources to achieve a target level of customer service at the lowest possible cost. It has been recognized as a major key to success in commerce and industry, and continues to evolve radically and grow in importance in recent years. Warehousing, as one of the most costly elements of logistics, is often the central operation in most logistics networks. Its successful management is critical in terms of both cost and service. In this thesis, two problem areas in warehouse logistics are studied: stock loading and order picking. Stock loading is an essential operation in modern logistics. Improvement on container capacity utilization and loading efficiency significantly reduces costs. For a given set of boxes in different sizes and an unlimited number of identical containers, the basic cargo loading problem is to determine the minimum number of containers required. The problem is proven NP-hard. To tackle this problem, a Tabu search optimization with a tree-based cargo loading algorithm as its inner heuristic is proposed. This approach has flexibility in taking different box conditions into consideration, and can find better solutions on average than other recent meta- or heuristic algorithms. Decreasing order sizes and increasing fuel costs provide a strong incentive for the inner-city truck loading operation to utilize containe