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http://hdl.handle.net/10397/5756
Title: | A multi agent based model for airport service planning | Authors: | Ip, WH Cho, WSV Chung, N Ho, TS |
Issue Date: | 2010 | Source: | International journal of engineering business management, 2010, v. 2, no. 2, p. 93-100 | Abstract: | Aviation industry is highly dynamic and demanding in nature that time and safety are the two most important factors while one of the major sources of delay is aircraft on ground because of it complexity, a lot o fmachinery like vehicles are involved and lots of communication are involved. As one of the aircraft ground services providers in Hong Kong International Airport, China Aircraft Services Limited (CASL) aims to increase competitiveness by better its service provided while minimizing cost is also needed. One of the ways is to optimize the number of maintenance vehicles allocated in order to minimize chance of delay and also operating costs. In the paper, an agent-based model is proposed for support decision making in vehicle allocation. The overview of the aircrafts ground services procedures is firstly mentioned with different optimization methods suggested by researchers. Then, the agent-based approach is introduced and in the latter part of report and a multi-agent system is built and proposed which is decision supportive for CASL in optimizing the maintenance vehicles’ allocation. The application provides flexibility for inputting number of different kinds of vehicles, simulation duration and aircraft arrival rate in order to simulation different scenarios which occurs in HKIA. | Keywords: | Multi agent Airport service planning Vehicle allocation Optimization Simulation |
Publisher: | SAGE Publications | Journal: | International journal of engineering business management | EISSN: | 1847-9790 | DOI: | 10.5772/9718 | Rights: | The article is licensed under a Creative Commons Attribution 3.0 Unported License <http://creativecommons.org/licenses/by/3.0/> |
Appears in Collections: | Journal/Magazine Article |
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Ip_Multi_Agent_Airport.pdf | 1.08 MB | Adobe PDF | View/Open |
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