A Study of Airline Fuel Planning Optimization Using R-Ga

Author:

Okafor Ekene Gabriel1,Uhuegho Osaretin Kole2,Manshop Christopher2,Jemitola Paul Olugbeji1,Ubadike Osichinaka Chiedu1

Affiliation:

1. Air Force Institute of Technology, NAF Base Kaduna

2. Nigerian College of Aviation Technology

Abstract

In this study, airline planning optimization problem based on ferry strategy was considered. Cost was the study objective function subject to forty equality and inequality constraints. Regression analysis as well a genetic algorithm (GA) was used to solve the problem. The mathematical relationship between flight fuel consumption and flight time was established using regression analysis, while GA was used for the optimization. The established mathematical model was used to predict the fuel consumption for the twenty scheduled flight consider based on their respective flight time. The result was found to be satisfactory, as optimal fuel lift plan was achieved in approximately twenty seconds of program run time, as against the large time usually spend using human effort to solve the fuel planning problem. The optimized fuel lift plan was compared with the actual fuel lift plan executed by the airline for the twenty scheduled flight considered. The result revealed thirty percent savings using the optimized plan in comparison to the actual fuel lift plan executed by the airline.

Publisher

Trans Tech Publications, Ltd.

Reference18 articles.

1. Air Transport Association. http://www.airlines.org/News/Releases/ Pages/news_7-28-2011.aspx. Accessed Nov. 7, (2011).

2. Lahey, W., and P. Heilbron. Aviation Fueling at Large Airports: Negotiating Workable Agreements Between Airlines and Airport Proprietors. Transportation Law Journal, Vol. 35, 2008, p.245–261.

3. Lawicki, D. Jet Fuel Characteristics: Performance Engineer Operations, Flight Operations Engineering. (2002).

4. Research and Innovative Technology Administration. http://www. transtats.bts.gov/ fuel.asp?pn=1. Accessed Feb. 2, (2019).

5. Research and Innovative Technology Administration. http://www.bts. gov/xml/fuel/report/ src/tableversion.xml. Accessed Feb. 2, (2019).

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