Data-driven optimization for Dallas Fort Worth International Airport deicing activities

Huiyuan Fan, Prashant K. Tarun, Victoria C.P. Chen, Dachuan T. Shih, Jay M. Rosenberger, Seoung Bum Kim, Robert A. Horton

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Airplane deicing is a safety measure to eliminate/prevent icing on airplanes that can lead to airflow disruption and emergency conditions. Aircraft deicing/anti-icing fluids (ADF) are high in glycol content. At Dallas Fort Worth International Airport (DFW), the major aircraft deicing activities are conducted at designated deicing pads called Source Isolation Deicing Sites, where ADF run-off can be captured and conveyed into the airport’s glycol collection system. A portion of ADF drips from the aircraft during taxiing and shears off the aircraft during take-off, entering nearby waterways without treatment. Glycol acts as a nutrient for bacteria in the airport’s receiving waterways, resulting in an increase in bacterial growth and a subsequent reduction in dissolved oxygen (DO), potentially endangering aquatic life. This paper proposes a prototype data-driven deicing activities management framework for DFW to address the complexity of airport deicing operations and its impacts. The proposed framework uses stochastic dynamic programming (SDP) to assign airplanes in each hour to deicing pad locations, so as to maximize DO in the receiving waters, subject to airport constraints. Some data were artificially generated using the available knowledge of airport operations. The state transition equations in SDP were estimated. The proposed framework was demonstrated using three cases during major deicing events. Improvements in DO compared with actual DO recorded in the data were mixed; however, the results motivated DFW to implement a new data collection process to replace the artificially-generated data, so that a more accurate optimization could be conducted in the future.

Original languageEnglish
Pages (from-to)1-24
Number of pages24
JournalAnnals of Operations Research
DOIs
Publication statusAccepted/In press - 2017 Dec 28

Fingerprint

Airports
Aircraft
Stochastic dynamic programming
Emergency
Bacteria
Air flow
Nutrients
Safety measures
Water
Isolation
Management activities
Data collection
Disruption
Prototype

Keywords

  • Airport deicing
  • Data-driven optimization
  • Dissolved oxygen
  • Glycol
  • Stochastic dynamic programming
  • Water quality

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Management Science and Operations Research

Cite this

Fan, H., Tarun, P. K., Chen, V. C. P., Shih, D. T., Rosenberger, J. M., Kim, S. B., & Horton, R. A. (Accepted/In press). Data-driven optimization for Dallas Fort Worth International Airport deicing activities. Annals of Operations Research, 1-24. https://doi.org/10.1007/s10479-017-2747-1

Data-driven optimization for Dallas Fort Worth International Airport deicing activities. / Fan, Huiyuan; Tarun, Prashant K.; Chen, Victoria C.P.; Shih, Dachuan T.; Rosenberger, Jay M.; Kim, Seoung Bum; Horton, Robert A.

In: Annals of Operations Research, 28.12.2017, p. 1-24.

Research output: Contribution to journalArticle

Fan, Huiyuan ; Tarun, Prashant K. ; Chen, Victoria C.P. ; Shih, Dachuan T. ; Rosenberger, Jay M. ; Kim, Seoung Bum ; Horton, Robert A. / Data-driven optimization for Dallas Fort Worth International Airport deicing activities. In: Annals of Operations Research. 2017 ; pp. 1-24.
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