A robust mathematical model and heuristic algorithms for integrated aircraft routing and scheduling, with consideration of fleet assignment problem

2017 ◽  
Vol 58 ◽  
pp. 21-30 ◽  
Author(s):  
Amin Jamili
Keyword(s):  
Mathematical Model ◽  
Assignment Problem ◽  
Heuristic Algorithms ◽  
Fleet Assignment ◽  
Aircraft Routing ◽  
Routing And Scheduling ◽  
Fleet Assignment Problem ◽  
Aircraft Routing And Scheduling

scholarly journals Aircraft Routing and Scheduling: a Case Study in an Airline Company

2011 ◽  
Vol 1 (1) ◽  
pp. 27-43 ◽  
Author(s):  
Aslan Deniz KARAOGLAN ◽  
Demet GONEN ◽  
Emine UCMUS
Keyword(s):  
Mathematical Model ◽  
Scheduling Problem ◽  
Aircraft Routing ◽  
Routing And Scheduling ◽  
Daily Schedule ◽  
Cargo Transportation ◽  
Aircraft Routing And Scheduling ◽  
Implementation Steps ◽  
Airline Company

A major problem faced by every airline is to construct a daily schedule for a heterogeneous aircraft fleet. In the present paper implementation of aircraft routing and scheduling for cargo transportation, known as one of the scheduling problem in transportation, in an air-line is presented. First, problems faced by the company are defined and then implementation steps and expected improvements that will result from carrying out the solution of mathematical model of the problem are given in detail. The purpose of this paper is to describe, analyze and evaluate a case study of how an aircraft scheduling was managed in an air-line.

scholarly journals Study on Fleet Assignment Problem Model and Algorithm

2013 ◽  
Vol 2013 ◽  
pp. 1-5
Author(s):  
Yaohua Li ◽  
Na Tan
Keyword(s):  
Assignment Problem ◽  
Production Data ◽  
Revenue Maximization ◽  
Mutation Operator ◽  
Fleet Assignment ◽  
Problem Model ◽  
Passenger Flows ◽  
Fleet Assignment Problem ◽  
The Difference ◽  
Crossover And Mutation

The Fleet Assignment Problem (FAP) of aircraft scheduling in airlines is studied, and the optimization model of FAP is proposed. The objective function of this model is revenue maximization, and it considers comprehensively the difference of scheduled flights and aircraft models in flight areas and mean passenger flows. In order to solve the model, a self-adapting genetic algorithm is supposed to solve the model, which uses natural number coding, adjusts dynamically crossover and mutation operator probability, and adopts intelligent heuristic adjusting to quicken optimization pace. The simulation with production data of an airline shows that the model and algorithms suggested in this paper are feasible and have a good application value.

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