標題: The optimal location of airport fire stations: A fuzzy multi-objective programming and revised genetic algorithm approach
作者: Tzeng, GH
Chen, YW
運輸與物流管理系 註:原交通所+運管所
Department of Transportation and Logistics Management
關鍵字: fuzzy;multi-objective;aircraft accidents;airport;fire station;location;combinatorial optimization;genetic algorithm
公開日期: 1999
摘要: As the global aviation business expands rapidly, issues of aviation safety become correspondingly important. In turn, aviation safety should be more emphasized. The crashes of China Airlines planes at Nagoya (Japan) international airport in 1994, and near Taipei's international airport in 1998, caused airport authorities around the world to pay closer attention to rescue and fire-protection plans at their airports. Our research reveals that the location and number of fire stations at an international airport is an important factor in its fire protection capability. However, if the sites of the fire stations are not appropriately planned and located, fire engines and crews cannot arrive at the accident area in a timely manner. Similarly, if the number of fire stations at an airport is not sufficient, fires caused by aircraft accidents may take longer to be extinguished, resulting in more injuries and fatalities. Therefore, a location model based on a fuzzy multi-objective approach is proposed in this paper. This model can help in determining the optimal number and sites of fire stations at an international airport, and can also assist the relevant authorities in drawing up optimal locations for fire stations. Finally, because of the combinatorial complexity of our model, a genetic algorithm (GA) is employed and compared with the enumeration method. The study results show that our revised CA is comparatively effective in resolution and that our model can be applied to the optimal location of other emergency facilities.
URI: http://hdl.handle.net/11536/31616
ISSN: 0308-1060
期刊: TRANSPORTATION PLANNING AND TECHNOLOGY
Volume: 23
Issue: 1
起始頁: 37
結束頁: 55
Appears in Collections:Articles


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