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Title: Modeling and solving a bi-objective airport slot scheduling problem
Authors: Androutsopoulos, Konstantinos N.
Manousakis, Eleftherios G.
Madas, Michael
Type: Article
Subjects: FRASCATI::Social sciences::Economics and Business::Business and Management
Keywords: Heuristics
Multiple criteria analysis
Project scheduling
Airport slot allocation
Issue Date: Jul-2020
Publisher: ScienceDirect
Source: European Journal of Operational Research
Volume: 284
Issue: 1
First Page: 135
Last Page: 151
Abstract: The strategic airport slot allocation problem concerns the scheduling of airlines’ requests for landings and take-offs at congested airports for a series of days within a given scheduling season. Relevant scheduling models dealing with the strategic airport slot allocation problem have employed various combinations of the total schedule displacement criterion with several variations of acceptability metrics. However, most variations of schedule displacement pursued in existing literature do not thoroughly capture the real-world scheduling practice, and, most importantly, do not guarantee the allocation of acceptable/tolerable or viable displacement among competing airlines’ slot requests. In this paper, we propose the formulation of the strategic airport slot allocation problem as a bi-objective resource constrained project scheduling problem with partially renewable resources and non-regular objective functions. We employ two non-regular performance criteria: (i) the total earliness-tardiness and (ii) a dispersion measure aiming to alleviate over-displaced requests. Α novel hybrid heuristic algorithm integrating the Objective Feasibility Pump (FP) algorithm with the Large Neighborhood Search technique (LNS) is proposed. We generate a set of new problem instances originating from the patterns of a data set of actual slot requests for a Greek Regional Airport (GRA) to assess the performance of the algorithm. The computational results indicate that the proposed algorithm is reasonably accurate, and it has the capability to approximate the entire efficient frontier of the problem.
ISSN: 0377-2217
Other Identifiers: 10.1016/j.ejor.2019.12.008
Appears in Collections:Department of Applied Informatics

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