Recoverable robust single day aircraft maintenance routing problem

Aircraft maintenance planning is of critical importance to the safe and efficient operations of an airline. It is common to solve the aircraft routing and maintenance planning problems many months in advance, with the solution spanning multiple days. An unfortunate consequence of this approach is the possible infeasibility of the maintenance plan due to frequent perturbations occurring in operations. There is an emerging concept that focuses on the generation of aircraft routes for a single day to ensure maintenance coverage that night, alleviating the effects of schedule perturbations from preceding days. In this paper, we present a novel approach to ensure that a sufficient number of aircraft routes are provided each day so maintenance critical aircraft receive maintenance that night. By penalising the under supply of routes terminating at maintenance stations from each overnight airport, we construct a single day routing to provide the best possible maintenance plan. This single day aircraft maintenance routing problem (SDAMRP) is further protected from disruptions by applying the recoverable robustness framework. To efficiently solve the recoverable robust SDAMRP acceleration techniques, such as identifying Pareto-optimal cuts and a trust region approach, have been applied. The SDAMRP is evaluated against a set of flight schedules and the results demonstrate a significantly improved aircraft maintenance plan. Further, the results demonstrate the magnitude of recoverability improvement that is achieved by employing recoverable robustness to the SDAMRP.

[1]  Michel Gendreau,et al.  Accelerating Benders Decomposition by Local Branching , 2009, INFORMS J. Comput..

[2]  Andrzej Ruszczynski,et al.  A regularized decomposition method for minimizing a sum of polyhedral functions , 1986, Math. Program..

[3]  Mattias Grönkvist,et al.  The Tail Assignment Problem , 2005 .

[4]  George L. Nemhauser,et al.  A Robust Fleet-Assignment Model with Hub Isolation and Short Cycles , 2004, Transp. Sci..

[5]  Ali Haghani,et al.  An optimization model for aircraft maintenance scheduling and re-assignment , 2003 .

[6]  Zhe Liang,et al.  The Aircraft Maintenance Routing Problem , 2009 .

[7]  DunbarMichelle,et al.  Robust Airline Schedule Planning , 2012 .

[8]  Jean-François Cordeau,et al.  Benders Decomposition for Simultaneous Aircraft Routing and Crew Scheduling , 2000, Transp. Sci..

[9]  BarnhartCynthia,et al.  Planning for Robust Airline Operations , 2006 .

[10]  Marcial Lapp,et al.  Modifying lines-of-flight in the planning process for improved maintenance robustness , 2012, Comput. Oper. Res..

[11]  A. M. Geoffrion,et al.  Multicommodity Distribution System Design by Benders Decomposition , 1974 .

[12]  Gary Froyland,et al.  The Recoverable Robust Tail Assignment Problem , 2014, Transp. Sci..

[13]  Guy Desaulniers,et al.  Aircraft routing under different business processes , 2009 .

[14]  Nikolaos Papadakos,et al.  Practical enhancements to the Magnanti-Wong method , 2008, Oper. Res. Lett..

[15]  Niklaus Eggenberg,et al.  Combining Robustness and Recovery for Airline Schedules , 2009 .

[16]  François Soumis,et al.  An integrated aircraft routing, crew scheduling and flight retiming model , 2005, Comput. Oper. Res..

[17]  I. Dovica,et al.  Robust Tail Assignment , 2010 .

[18]  Jean-François Cordeau,et al.  A computational study of Benders decomposition for the integrated aircraft routing and crew scheduling problem , 2003, Comput. Oper. Res..

[19]  Thomas L. Magnanti,et al.  Accelerating Benders Decomposition: Algorithmic Enhancement and Model Selection Criteria , 1981, Oper. Res..

[20]  Ravindra K. Ahuja,et al.  Network Flows: Theory, Algorithms, and Applications , 1993 .

[21]  Jonathan F. Bard,et al.  Flight Scheduling and Maintenance Base Planning , 1989 .

[22]  Matteo Fischetti,et al.  A note on the selection of Benders’ cuts , 2010, Math. Program..

[23]  Nikolaos Papadakos,et al.  Integrated airline scheduling , 2009, Comput. Oper. Res..

[24]  M. Laughton,et al.  Large-scale mixed integer programming: Benders-type heuristics , 1984 .

[25]  George L. Nemhauser,et al.  Flight String Models for Aircraft Fleeting and Routing , 1998, Transp. Sci..

[26]  Cynthia Barnhart,et al.  Planning for Robust Airline Operations: Optimizing Aircraft Routings and Flight Departure Times to Minimize Passenger Disruptions , 2006, Transp. Sci..

[27]  Jonathan F. Bard,et al.  Balancing user preferences for aircraft schedule recovery during irregular operations , 2000 .

[28]  George L. Nemhauser,et al.  The aircraft rotation problem , 1997, Ann. Oper. Res..

[29]  Matthias Ehrgott,et al.  An iterative approach to robust and integrated aircraft routing and crew scheduling , 2010, Comput. Oper. Res..

[30]  Gary Froyland,et al.  Robust Airline Schedule Planning: Minimizing Propagated Delay in an Integrated Routing and Crewing Framework , 2012, Transp. Sci..

[31]  John-Paul Clarke,et al.  Approaches to incorporating robustness into airline scheduling , 2000 .

[32]  Marc Goetschalckx,et al.  A stochastic programming approach for supply chain network design under uncertainty , 2004, Eur. J. Oper. Res..

[33]  Rolf H. Möhring,et al.  The Concept of Recoverable Robustness, Linear Programming Recovery, and Railway Applications , 2009, Robust and Online Large-Scale Optimization.

[34]  Stephen J. Wright,et al.  Decomposition Algorithms for Stochastic Programming on a Computational Grid , 2001, Comput. Optim. Appl..

[35]  Graham Tanner,et al.  European airline delay cost reference values , 2011 .

[36]  Jacques F. Benders,et al.  Partitioning procedures for solving mixed-variables programming problems , 2005, Comput. Manag. Sci..