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A k-best schedule algorithm for supporting airport slot scheduling

Research output: Contribution to conference - Without ISBN/ISSN Poster

Published
Publication date26/09/2019
Original languageEnglish
EventLUMS Research Conference 2019 - Lancaster University, Lancaster, United Kingdom
Duration: 26/09/2019 → …
https://www.lancaster.ac.uk/lums/research/events/lums-research-conference-2019

Conference

ConferenceLUMS Research Conference 2019
CountryUnited Kingdom
CityLancaster
Period26/09/19 → …
Internet address

Abstract

The increased demand for airline travel coupled with the slow implementation of airport capacity expansion plans, hinder the growth potential of global air transport inflicting vast costs to passengers, airlines and airports. As a short-term response, airport slot allocation is used for the efficient administration of airline demand for congested airport resources. Airport slot allocation is carried out by appointed slot schedule coordinators which take into account a complex regulatory framework and various objectives. However, multi-objective scheduling of airport slots becomes a challenge when the decision makers, i.e. airport slot coordinators, have to select airport slot schedules by balancing multiple conflicting objectives. The complexity of proposing airport slot schedules is further increased by the regulations which acknowledge different decision levels. These levels represent a well-defined hierarchy of different slot request priorities which requires airport slot coordinators to treat each of them sequentially. Although many studies have addressed the challenge of producing the set of nondominated airport slot schedules, none of them focused on proposing solution approaches which can elicit a single slot-scheduling solution. To address this issue, we propose a novel solution approach. First, for each slot request priority, we formulate and solve a quadr-objective airport slot scheduling model that minimises the number of rejected slot requests, total schedule and maximum displacement, and the number of displaced slot requests. In particular, we minimise the number of slot request rejections and then, by using an efficient solution algorithm we produce the full set of nondominated points regarding the remaining objectives. Second, in order to select the most suitable schedule and proceed to the lower echelons of the slot request hierarchy, we apply a tractable, multi-criteria, decision-making technique that considers multiple quality assessment criteria and can encompass stakeholders’ preferences. Third, aiming to improve the schedule’s acceptability by the air carrier perspective, for each priority we filter out solutions which are dominated with respect to the airlines’ objectives. After parsing all decision levels, we merge the schedules of each priority and construct the aggregate airport schedule. In the case that stakeholders require multiple solutions in order to choose, our solution approach can be tuned using a suitable parameter k so as to produce the k-best schedules. Our computational results on a medium sized European airport suggest that the proposed algorithm can produce high-quality airport slot schedules within tractable computational times. Through the consideration of individual airlines’ objectives and multiple aggregate schedule quality metrics, decision makers reach more informed, and thus more acceptable slot scheduling decisions.