GS5-3 Review on computational techniques in solving aircraft landing problem

Title:	GS5-3 Review on computational techniques in solving aircraft landing problem
Publication:	ICAROB2018
Volume:	23
Pages:	128-131
ISSN:	2188-7829
DOI:	10.5954/ICAROB.2018.GS5-3
Author(s):	Aminurafiuddin Zulkifli, Nor Azlina Ab Aziz, Nor Hidayati Abdul Aziz, Zuwairie Ibrahim, Norrima Mokhtar
Publication Date:	February 2, 2018
Keywords:	aircraft landing problem, computational intelligence, evolutionary algorithms, swarm intelligence, scheduling, runway operation
Abstract:	The problem of sequencing and scheduling arriving aircraft landing is commonly known as aircraft landing problem (ALP). This problem, due to various constraints such as the number of arriving aircrafts, the number of runways, the mode of runway operation, the type of arriving aircrafts, the minimum separation between each arriving aircraft, and the weather condition, is considered to be a NP-hard problem. Therefore, it is almost impossible to compute every possible solution and computational intelligence methods had been adopted to solve ALP. In this paper, we review the computational intelligence techniques used in ALP. The main techniques include the evolutionary algorithms namely; genetic algorithm, genetic programming, scatter search and bionomic algorithm, the swarm intelligence algorithms like particle swarm optimization and ant colony optimization and also other methods such as the constrained position shifting and dynamic programming.
PDF File:	https://alife-robotics.co.jp/members2018/icarob/data/html/data/GS_pdf/GS5/GS5-3.pdf
Copyright:	© The authors. This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited. See for details: https://creativecommons.org/licenses/by-nc/4.0/

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