Continuous Flight Rescheduling Problem Resolution Based on Genetic Algorithms

This present paper deals with air traffic management problem for the continuous flights with stopover and returning at initial airport. The initial scheduling is disrupted by poor weather conditions, which may change over time. For this problem, we consider the air traffic as a discrete event system where the rescheduled flights are modelled by time Petri net tool. As a resolution approach for this problem, a genetic algorithm is introduced where a new encoding of flight plans is proposed. The feasibility of generated solutions, by genetic algorithm, is checked by means of our recently approach so-called Time Reduced Ordered Binary Decision Diagrams (TROBDDs). A numerical example is provided to show that the proposed genetic algorithm exhibits a much better quality of routing solution and a much higher rate of convergence than other algorithms.

[1]  Mitsuo Gen,et al.  A genetic algorithm based approach to vehicle routing problem with simultaneous pick-up and deliveries , 2010, The 40th International Conference on Computers & Indutrial Engineering.

[2]  Amedeo R. Odoni,et al.  Dynamic Ground-Holding Policies for a Network of Airports , 1994, Transp. Sci..

[3]  Peter Y. K. Cheung,et al.  Improved variable ordering of BDDs with novel genetic algorithm , 1996, 1996 IEEE International Symposium on Circuits and Systems. Circuits and Systems Connecting the World. ISCAS 96.

[4]  Giovanni Andreatta,et al.  Aircraft Flow Management under Congestion , 1987, Transp. Sci..

[5]  Lai Soon Lee,et al.  Optimised crossover genetic algorithm for capacitated vehicle routing problem , 2012 .

[6]  Nidhal Rezg,et al.  An efficient hybrid approach for resolving the aircraft routing and rescheduling problem , 2018 .

[7]  E. Pastor,et al.  Symbolic Analysis of Bounded Petri Nets , 2001, IEEE Trans. Computers.

[8]  R. Rudell.  Dynamic variable ordering for ordered binary decision diagrams , 1993, Proceedings of 1993 International Conference on Computer Aided Design (ICCAD).

[9]  Octavio Richetta.  Ground holding strategies for air traffic control under uncertainty , 1991 .

[10]  Jan K. Brueckner,et al.  A MODEL OF SCHEDULING IN AIRLINE NETWORKS: HOW A HUB-AND-SPOKE SYSTEM AFFECTS FLIGHT FREQUENCY, FARES AND WELFARE , 2001 .

[11]  Larry J. Eshelman,et al.  The CHC Adaptive Search Algorithm: How to Have Safe Search When Engaging in Nontraditional Genetic Recombination , 1990, FOGA.

[12]  Chandrasekharan Rajendran,et al.  A multiobjective genetic algorithm for scheduling a flexible manufacturing system , 2003 .

[13]  Jacco M. Hoekstra,et al.  Designing for safety: the 'free flight' air traffic management concept , 2002, Reliab. Eng. Syst. Saf..

[14]  Beate Bollig,et al.  Improving the Variable Ordering of OBDDs Is NP-Complete , 1996, IEEE Trans. Computers.

[15]  Dimitris Bertsimas,et al.  The Air Traffic Flow Management Problem with Enroute Capacities , 1998, Oper. Res..

[16]  Nidhal Rezg,et al.  State Space Search for Safe Time Petri Nets Based on Binary Decision Diagrams Tools: Application to Air Traffic Flow Management Problem , 2016 .

[17]  Masahiro Fujita,et al.  Variable ordering algorithms for ordered binary decision diagrams and their evaluation , 1993, IEEE Trans. Comput. Aided Des. Integr. Circuits Syst..

[18]  A. Odoni.  The Flow Management Problem in Air Traffic Control , 1987 .

[19]  Nidhal Rezg,et al.  New approach for air traffic management based on control theory , 2014 .

[20]  M. S. Eby,et al.  Free flight separation assurance using distributed algorithms , 1999, 1999 IEEE Aerospace Conference. Proceedings (Cat. No.99TH8403).

[21]  Lin Lin,et al.  Multiobjective evolutionary algorithm for manufacturing scheduling problems: state-of-the-art survey , 2014, J. Intell. Manuf..

[22]  Laureano F. Escudero,et al.  On air traffic flow management with rerouting. Part II: Stochastic case , 2012, Eur. J. Oper. Res..