A multi-objective fuzzy optimization model for multi-type aircraft flight scheduling problem

This study proposes a multi-objective optimization model for an Aircraft Flight Scheduling Problem (AFSP) for assigning a set of aircraft located at different airports to conduct all flight trips. The proposed model features each flight trip with its own special aircraft type and fuzzy flight time. Moreover, a flight trip with a small aircraft being covered by a larger one is fully accounted for in the model. The model can effectively reduce the number of aircraft and achieve the minimum total idle time for adjacent flight trips covered by an aircraft. A novel heuristic algorithm based on the Non-dominated Sorting Genetic Algorithm (NSGA-II) is further designed to yield meta-optimal solutions efficiently for such a Non-deterministic Polynomial (NP) problem. Finally, a real airline scheduling example in China is conducted using CPLEX and the proposed heuristic algorithm to evaluate the difference between the proposed and traditional models. The results show that the given scheduling problem effectively enhances the operational efficiency of the aircraft fleet. First published online 28 January 2025

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Publication Details

Journal
Transport
Published
2024-12-31
DOI
https://doi.org/10.3846/transport.2024.20536
Citations
57
Primary Topic
Vehicle Routing Optimization Methods
Type
article
Field-Weighted Citation Impact
19.89
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article

A multi-objective fuzzy optimization model for multi-type aircraft flight scheduling problem

Shangwen Yang, Wei Wu, Bo Sun, Wei Ming
57 citations
Transport
Vehicle Routing Optimization Methods
19.89
article

A multi-objective fuzzy optimization model for multi-type aircraft flight scheduling problem

Shangwen Yang, Wei Wu, Bo Sun, Wei Ming
article en
57 citations

Abstract

This study proposes a multi-objective optimization model for an Aircraft Flight Scheduling Problem (AFSP) for assigning a set of aircraft located at different airports to conduct all flight trips. The proposed model features each flight trip with its own special aircraft type and fuzzy flight time. Moreover, a flight trip with a small aircraft being covered by a larger one is fully accounted for in the model. The model can effectively reduce the number of aircraft and achieve the minimum total idle time for adjacent flight trips covered by an aircraft. A novel heuristic algorithm based on the Non-dominated Sorting Genetic Algorithm (NSGA-II) is further designed to yield meta-optimal solutions efficiently for such a Non-deterministic Polynomial (NP) problem. Finally, a real airline scheduling example in China is conducted using CPLEX and the proposed heuristic algorithm to evaluate the difference between the proposed and traditional models. The results show that the given scheduling problem effectively enhances the operational efficiency of the aircraft fleet. First published online 28 January 2025

TransportVol. 39(4)
Nantong University (CN), Civil Aviation University of China (CN), Institute of Electronics (CN)
Openalex Percentile: Top 0%
Vehicle Routing Optimization Methods
19.89
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