| Author: | Shum, Chun-chi |
| Title: | Airfreight cargo planning |
| Degree: | M.Sc. |
| Year: | 2010 |
| Subject: | Hong Kong Polytechnic University -- Dissertations Cargo handling -- Data processing Aeronautics, Commercial -- Freight -- Data processing Freight and freightage |
| Department: | Department of Computing |
| Pages: | vii, 50 leaves : ill. ; 30 cm. |
| Language: | English |
| Abstract: | Currently, most of the air freight forwarders still generate loading plans individually. We propose to streamline effectiveness of cargo handling with a single site cargo automation planning design and a multi-site collaborative solution. Our approach is based on the intelligent agent technology, bin packing heuristic and the inter-site workflow protocol. The major problems being tackled are (1) how to make the best estimation of the equipments required; (2) how to load the cargoes under the minimum cost in the standalone site case and (3) optimization of space and cargo loading cost under the multiple sites case. A prototype has been developed to illustrate the operations of our framework. The report consists of three major areas. Firstly, we give a thoughtful explanation of the air freight forwarding industry with special attention on the cargo planning process. Then, we would like to explore the possibility of using two technologies, bin packing and intelligent agent, in the air freight cargo planning. The second part of the project is emphasized on automation of the air cargo consol planning generation process in a single site. In the third part of the project, we explored the possibility to collaborate multiple sites in the cargo planning process. We design an agent-based framework of multi-site cargo planning system for the air freight forwarding industry. |
| Rights: | All rights reserved |
| Access: | restricted access |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| b23526385.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 2.17 MB | Adobe PDF | View/Open |
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