Robust resource planning for aircraft ground operations

Yagmur S. Gök; Daniel Guimarans; Peter J. Stuckey; Maurizio Tomasella; Cemalettin Ozturk

doi:10.1007/978-3-030-58942-4_15

Robust resource planning for aircraft ground operations

Yagmur S. Gök^*, Daniel Guimarans, Peter J. Stuckey, Maurizio Tomasella, Cemalettin Ozturk

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract / Description of output

Aircraft turnaround scheduling and airport ground services team/equipment planning directly concern both the airport operator and service providers. We first ensure airport-wide global optimality by solving a resource-constrained project scheduling problem (RCPSP) for minimal overall delays. We then support decentralized allocation of teams/vehicles to flights, independently by each service provider. Either a multiple traveling salesman problem with time-windows (mTSPTW), or a vehicle routing problem with time-windows (VRPTW) are solved for this purpose, by taking advantage of both constraint programming (CP) and mixed integer programming (MIP) solvers. We also exploit these models in a matheuristic approach based on large neighborhood search used to reach good solutions in reasonable time for real-world instances. Unlike the classical VRP objective of minimizing traveling time, we maximize the total slack time between team visits, and show that doing this fosters robustness of the generated plans. We assess the robustness of solutions through a discrete-event simulation model, and conclude by validating our approach with data provided by a major ground handling company for a day of operations at Barcelona El Prat Airport.

Original language	English
Title of host publication	Integration of Constraint Programming, Artificial Intelligence, and Operations Research - 17th International Conference, CPAIOR 2020, Proceedings
Editors	Emmanuel Hebrard, Nysret Musliu
Publisher	Springer
Pages	222-238
Number of pages	17
ISBN (Print)	9783030589417
DOIs	https://doi.org/10.1007/978-3-030-58942-4_15
Publication status	Published - 19 Sept 2020
Event	17th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, CPAIOR 2020 - Vienna, Austria Duration: 21 Sept 2020 → 24 Sept 2020

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12296 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	17th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, CPAIOR 2020
Country/Territory	Austria
City	Vienna
Period	21/09/20 → 24/09/20

Keywords / Materials (for Non-textual outputs)

airport operations
aviation
optimization
routing
scheduling

Access to Document

10.1007/978-3-030-58942-4_15

Cite this

Gök, Y. S., Guimarans, D., Stuckey, P. J., Tomasella, M., & Ozturk, C. (2020). Robust resource planning for aircraft ground operations. In E. Hebrard, & N. Musliu (Eds.), Integration of Constraint Programming, Artificial Intelligence, and Operations Research - 17th International Conference, CPAIOR 2020, Proceedings (pp. 222-238). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12296 LNCS). Springer. https://doi.org/10.1007/978-3-030-58942-4_15

Gök, Yagmur S. ; Guimarans, Daniel ; Stuckey, Peter J. et al. / Robust resource planning for aircraft ground operations. Integration of Constraint Programming, Artificial Intelligence, and Operations Research - 17th International Conference, CPAIOR 2020, Proceedings. editor / Emmanuel Hebrard ; Nysret Musliu. Springer, 2020. pp. 222-238 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{9fae9766b1c34793a985353d9bcf8e70,

title = "Robust resource planning for aircraft ground operations",

abstract = "Aircraft turnaround scheduling and airport ground services team/equipment planning directly concern both the airport operator and service providers. We first ensure airport-wide global optimality by solving a resource-constrained project scheduling problem (RCPSP) for minimal overall delays. We then support decentralized allocation of teams/vehicles to flights, independently by each service provider. Either a multiple traveling salesman problem with time-windows (mTSPTW), or a vehicle routing problem with time-windows (VRPTW) are solved for this purpose, by taking advantage of both constraint programming (CP) and mixed integer programming (MIP) solvers. We also exploit these models in a matheuristic approach based on large neighborhood search used to reach good solutions in reasonable time for real-world instances. Unlike the classical VRP objective of minimizing traveling time, we maximize the total slack time between team visits, and show that doing this fosters robustness of the generated plans. We assess the robustness of solutions through a discrete-event simulation model, and conclude by validating our approach with data provided by a major ground handling company for a day of operations at Barcelona El Prat Airport.",

keywords = "airport operations, aviation, optimization, routing, scheduling",

author = "G{\"o}k, {Yagmur S.} and Daniel Guimarans and Stuckey, {Peter J.} and Maurizio Tomasella and Cemalettin Ozturk",

note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; 17th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, CPAIOR 2020 ; Conference date: 21-09-2020 Through 24-09-2020",

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doi = "10.1007/978-3-030-58942-4_15",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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Gök, YS, Guimarans, D, Stuckey, PJ, Tomasella, M & Ozturk, C 2020, Robust resource planning for aircraft ground operations. in E Hebrard & N Musliu (eds), Integration of Constraint Programming, Artificial Intelligence, and Operations Research - 17th International Conference, CPAIOR 2020, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12296 LNCS, Springer, pp. 222-238, 17th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, CPAIOR 2020, Vienna, Austria, 21/09/20. https://doi.org/10.1007/978-3-030-58942-4_15

Robust resource planning for aircraft ground operations. / Gök, Yagmur S.; Guimarans, Daniel; Stuckey, Peter J. et al.
Integration of Constraint Programming, Artificial Intelligence, and Operations Research - 17th International Conference, CPAIOR 2020, Proceedings. ed. / Emmanuel Hebrard; Nysret Musliu. Springer, 2020. p. 222-238 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12296 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Robust resource planning for aircraft ground operations

AU - Gök, Yagmur S.

AU - Guimarans, Daniel

AU - Stuckey, Peter J.

AU - Tomasella, Maurizio

AU - Ozturk, Cemalettin

PY - 2020/9/19

Y1 - 2020/9/19

N2 - Aircraft turnaround scheduling and airport ground services team/equipment planning directly concern both the airport operator and service providers. We first ensure airport-wide global optimality by solving a resource-constrained project scheduling problem (RCPSP) for minimal overall delays. We then support decentralized allocation of teams/vehicles to flights, independently by each service provider. Either a multiple traveling salesman problem with time-windows (mTSPTW), or a vehicle routing problem with time-windows (VRPTW) are solved for this purpose, by taking advantage of both constraint programming (CP) and mixed integer programming (MIP) solvers. We also exploit these models in a matheuristic approach based on large neighborhood search used to reach good solutions in reasonable time for real-world instances. Unlike the classical VRP objective of minimizing traveling time, we maximize the total slack time between team visits, and show that doing this fosters robustness of the generated plans. We assess the robustness of solutions through a discrete-event simulation model, and conclude by validating our approach with data provided by a major ground handling company for a day of operations at Barcelona El Prat Airport.

AB - Aircraft turnaround scheduling and airport ground services team/equipment planning directly concern both the airport operator and service providers. We first ensure airport-wide global optimality by solving a resource-constrained project scheduling problem (RCPSP) for minimal overall delays. We then support decentralized allocation of teams/vehicles to flights, independently by each service provider. Either a multiple traveling salesman problem with time-windows (mTSPTW), or a vehicle routing problem with time-windows (VRPTW) are solved for this purpose, by taking advantage of both constraint programming (CP) and mixed integer programming (MIP) solvers. We also exploit these models in a matheuristic approach based on large neighborhood search used to reach good solutions in reasonable time for real-world instances. Unlike the classical VRP objective of minimizing traveling time, we maximize the total slack time between team visits, and show that doing this fosters robustness of the generated plans. We assess the robustness of solutions through a discrete-event simulation model, and conclude by validating our approach with data provided by a major ground handling company for a day of operations at Barcelona El Prat Airport.

KW - airport operations

KW - aviation

KW - optimization

KW - routing

KW - scheduling

UR - http://www.scopus.com/inward/record.url?scp=85092180761&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-58942-4_15

DO - 10.1007/978-3-030-58942-4_15

M3 - Conference contribution

AN - SCOPUS:85092180761

SN - 9783030589417

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 222

EP - 238

BT - Integration of Constraint Programming, Artificial Intelligence, and Operations Research - 17th International Conference, CPAIOR 2020, Proceedings

A2 - Hebrard, Emmanuel

A2 - Musliu, Nysret

PB - Springer

T2 - 17th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, CPAIOR 2020

Y2 - 21 September 2020 through 24 September 2020

ER -

Gök YS, Guimarans D, Stuckey PJ, Tomasella M, Ozturk C. Robust resource planning for aircraft ground operations. In Hebrard E, Musliu N, editors, Integration of Constraint Programming, Artificial Intelligence, and Operations Research - 17th International Conference, CPAIOR 2020, Proceedings. Springer. 2020. p. 222-238. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-58942-4_15

Robust resource planning for aircraft ground operations

Abstract / Description of output

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Conference

Keywords / Materials (for Non-textual outputs)

Access to Document

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