An evolutionary approach for dynamic single-runway arrival sequencing and scheduling problem

Abstract

Aircraft arrival sequencing and scheduling is a classic problem in the air traffic control to ensure safety and order of the operations at the terminal area. Most of the related studies have formulated this problem as a static case and assume the information of all the flights is known in advance. However, the operation of the terminal area is actually a dynamic incremental process. Various kinds of uncertainties may exist during this process, which will make the scheduling decision obtained in the static environment inappropriate. In this paper, aircraft arrival sequencing and scheduling problem is tackled in the form of a dynamic optimization problem. An evolutionary approach, namely dynamic sequence searching and evaluation, is proposed. The proposed approach employs an estimation of distribution algorithm and a heuristic search method to seek the optimal landing sequence of flights. Compared with other related algorithms, the proposed method performs much better on several test instances including an instance obtained from the real data of the Beijing Capital International Airport.

Uma abordagem metaheurística para o sequenciamento de aeronaves para pouso e o aumento de capacidade de pista

“…Os dados teóricos encontrados na OR-Library e utilizados inicialmente no trabalho de Beasley et al (2000) são os mais utilizados. Para os trabalhos que utilizam dados reais, os seguintes aeroportos foram utilizados: Frankfurt (Trivizas, 1998;Lieder e Stolletz, 2016), Denver (Balakrishnan e Chandran, 2010), Detroit (Metropolitan Wayne County) (Sölveling et al, 2011;Andreeva-Mori et al, 2013), Londres (Heathrow) (Caccavale et al, 2014;Bennell et al, 2016;Lieder e Stolletz, 2016), Nova Iorque (John F. Kennedy, Newark e La Guardia (Jacquillat e Odoni, 2015), Milão (Linate) (Furini et al, 2015;Vasilyev et al, 2016;Sylejmani et al, 2017), Chengdu (Shuangliu) (Zhou e Jiang, 2015), Beijing (Ji et al, 2016), Roma (Fiumicino) (Sama et al, 2016) e Estocolmo (Arlanda) (Avella et al, 2017). Outros artigos usam uma combinação de dados teóricos e reais (Fahle et al, 2004;Ghoniem et al, 2014;Rodrıǵuez-Dıáz et al, 2017).…”

A Data-Driven Method for Arrival Sequencing and Scheduling Problem

“…During nearly three decades of development, the research on ASSP attracted considerable attention from many researchers. Some research treated the ASSP as a static case [3] and others as a dynamic case [4][5][6][7][8][9][10]; some research tackled the ASSP from a deterministic perspective and others from a stochastic perspective [11][12][13][14]; some research concerned the appeals of one single stakeholder (i.e., single-objective optimization) [15][16][17][18] and others multiple stakeholders (i.e., multiple-objectives optimization) [19][20][21][22][23]; some research solved the ASSP by exact solution methods [3,19,[24][25][26][27][28] (e.g., Beasley used solvers such as CPLEX and Briskorn used model language such as GAMS) and others by approximate solution methods [29], including the simulated annealing algorithm [18,30], genetic algorithm [31,32], ant colony optimization algorithm [33], imperialist competitive algorithm [34], local search algorithm [10], and so on; and some research only provided the optimized landing runway, sequence, and time, while others also proposed the advisories for air traffic controllers [22,[35][36][37].…”

An Improved Immunoglobulin-Based Artificial Immune System for the Aircraft Scheduling Problem With Alternate Aircrafts

“…Ji et al [15] first formulated the Aircraft scheduling problem as a constrained permutation-based problem and then proposed a sequence search and evaluation approach for the constrained permutation-based problem. Ji et al [16] tackled the aircraft arrival sequencing and scheduling problem with an evolutionary approach named dynamic sequence searching and evaluation. The approach employs an estimation of the distribution algorithm and a heuristic search method to seek the optimal or near optimal landing sequence of aircrafts.…”