This dissertation, "A Genetic Algorithm Based Approach for Air Cargo Loading Problem" by Niraj, Kumar, 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: Abstract of thesis entitled "A Genetic Algorithm Based Approach for Air Cargo Loading Problem" Submitted by Niraj KUMAR for the degree of Master of Philosophy at The University of Hong Kong in December 2006 Logistics processes are very important in enabling suppliers to provide the right product to the right customer at the right time and at the right cost. Logistics costs have an important influence on the final cost of the product. In today's global business environment, a cost effective logistics process is crucial for the success of suppliers. The uncertain demand pattern in competitive markets also demands a reliable logistics system capable of responding quickly to unforeseen developments. Air-logistics systems provide an effective solution for the faster and secure delivery of goods across the globe. Unlike land and marine transport systems, they tend to deal with more expensive and time-sensitive goods. Air transport helps to keep down associated inventory, warehousing and maintenance costs, but is normally a more expensive transport option than other transportation modes. Designing a cost effective air-logistics system is always a challenging and difficult task. In air-logistics systems, the loading of air cargos is an important step in estimating the transportation cost. The inefficient loading or packing of air cargos can result in unnecessary extra labour cost and extra delays in terms of unpacking and reloading of air cargos. This may further result in higher transportation costs and poor customer service. An intelligent decision-making system to tackle the air cargos loading process is currently in great demand from the air-freight forwarder industries. Although most of the warehousing and distribution processes are fully automated, the actual loading pattern of the air cargos still relies on on-the-spot decisions taken by ground operators, which results in underutilization of the empty space inside the containers. The aim of this study is to explore the complexities involved in air cargo loading problems and suggest a cost effective approach to tackle it. A Genetic Algorithm (GA) based hybrid optimization approach is proposed in this study for solving the air cargo loading problems. The hybrid approach includes the GA and a ranking based packing heuristic to decide the efficient packing strategy of the air cargos at possible minimal cost. In the proposed approach, GA searches for the possible good solutions whereas the packing heuristic checks the overall feasibility of the solution in context of the practical constraints. The GA based intelligent system is effective in providing the air cargo loading solutions at possible minimum transportation cost. A real-life industrial problem is discussed in this study to implement the proposed approach. The robustness and reliability of the proposed approach is verified and discussed in comparison with the real-life data set. (413 Words) DOI: 10.5353/th_b3857681 Subjects: Genetic algorithms Loading and unloading - Mathematical models Aeronautics, Commercial - Freight - Mathematical models Business logistics