Commercial airline companies are continuously seeking to implement strategies for minimizing costs of fuel for their flight routes as acquiring jet fuel represents a significant part of operating and managing expenses...
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Commercial airline companies are continuously seeking to implement strategies for minimizing costs of fuel for their flight routes as acquiring jet fuel represents a significant part of operating and managing expenses for airline activities.A nonlinearmixedbinary mathematical programming model for the airline fuel task is presented to minimize the total cost of refueling in an entire flight route *** model is enhanced to include possible discounts in fuel prices,which are performed by adding dummy variables and some restrictive constraints,or by fitting a suitable distribution function that relates prices to purchased *** obtained fuel plan explains exactly the amounts of fuel in gallons to be purchased from each airport considering tankering strategy while minimizing the pertinent cost of the whole flight *** relation between the amount of extra burnt fuel taken through tinkering strategy and the total flight time is also considered.A case study is introduced for a certain flight rotation in domestic US air transport *** mathematical model including stepped discounted fuel prices is *** problem has a stochastic nature as the total flight time is a random variable,the stochastic nature of the problem is realistic and more appropriate than the deterministic *** stochastic style of the problem is simulated by introducing a suitable probability distribution for the flight time duration and generating enough number of runs to mimic the probabilistic real *** similar real application problems are modelled as nonlinearmixedbinary ones that are difficult to handle by exact ***,metaheuristic approaches are widely used in treating such different optimization *** this paper,a gaining sharing knowledge-based procedure is used to handle the mathematical *** algorithm basically based on the process of gaining and sharing knowledge throughout the human *** generated simulation runs of
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