A simheuristic approach for solving the aircraft Recovery Problem with stochastic delays

Daniel Guimarans, Pol Arias, Wenjing Zhao

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearch

Abstract

Air transport operational disruptions arise when operations deviate from the original plan. Due to airlines network configuration, delays are rapidly propagated to connecting flights, substantially increasing unexpected costs for the airlines. The goal in these situations is therefore to minimise the impact of the disruption, reducing delays and the number of affected flights, crews and passengers. However, the reach of a specific disruption is not normally known or it is difficult to assess, increasing the complexity of the problem. In this work, we introduce a methodology based on a Large Neighbourhood Search metaheuristic and a Constraint Programming formulation to tackle the Aircraft
Recovery Problem with stochastic delays. We use simulation to help guiding the search, account for system’s variability, and evaluate solutions’ behaviour. We present some preliminary results on a set of instances with different sizes and characteristics, including some instances originating from real data.
Original languageEnglish
Title of host publicationMetaheuristics
Subtitle of host publicationProceeding of the MIC and MAEB 2017 Conferences
EditorsAbraham Duarte, Ana Viana, Angel Juan, Belén Mélian, Helena Ramalhinho
Place of PublicationBarcelona Spain
PublisherUniversitat Pompeu Fabra
Pages48-50
Number of pages3
ISBN (Electronic)9788469742751
Publication statusPublished - 2017
Externally publishedYes
EventMetaheuristics International Conference 2017 - Barcelona, Spain
Duration: 4 Jul 20177 Jul 2017
Conference number: 12th
http://mic2017.upf.edu/

Conference

ConferenceMetaheuristics International Conference 2017
Abbreviated titleMIC 2017
CountrySpain
CityBarcelona
Period4/07/177/07/17
Internet address

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