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Cluster Computing
Erschienen in: Cluster Computing 3/2018

23.02.2018

Flower pollination algorithm with runway balance strategy for the aircraft landing scheduling problem

verfasst von: Guo Zhou, Rui Wang, Yongquan Zhou

Erschienen in: Cluster Computing | Ausgabe 3/2018

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Abstract

Aircraft landing scheduling is a challenging problem in the field of air traffic, whose objective is to determine the best combination of assigning the sequence and corresponding landing time for a given set of aircraft to a runway, and then minimize the sum of the deviations of the actual and target landing times under the condition of safe landing. In this paper, a flower pollination algorithm embedded with runway balance is proposed to solve it. Context cognitive learning and runway balance strategy are devised here to enhance its searching ability. 36 scheduling instances are selected from OR-Library to validate its performance. The experimental results show that the proposed algorithm can get the optimal solutions for instances up to 100 aircrafts, and is also capable of obtaining better solutions compared with SS, BA and FCFS for instances up to 500 aircrafts in a shorter time.
Vorheriger Artikel Energy-efficient hybrid coherence protocol for multicore processors
Nächster Artikel EAD: elasticity aware deduplication manager for datacenters with multi-tier storage systems

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Metadaten
Titel
Flower pollination algorithm with runway balance strategy for the aircraft landing scheduling problem
verfasst von
Guo Zhou
Rui Wang
Yongquan Zhou
Publikationsdatum
23.02.2018
Verlag
Springer US
Erschienen in
Cluster Computing / Ausgabe 3/2018
Print ISSN: 1386-7857
Elektronische ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-018-2051-0

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