Greedy algorithms and metaheuristics for a multiple runway combined arrival-departure aircraft sequencing problem

Hançerlioğulları, Gülşah; Rabadi, Ghaith; Al-Salem, Mohammed; Kharbeche, Mohamed

doi:10.1016/j.jairtraman.2013.06.001

Cited by 86 publications

(57 citation statements)

References 26 publications

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“…Many runways use a mixed mode of operation, so it is necessary to consider takeoff aircrafts on the same runway to avoid accidents [12]. However, most studies ignored departing flights in the terminal area.…”

Section: Tendencymentioning

confidence: 99%

A Review for Aircraft Landing Problem

Wang

2018

MATEC Web Conf.

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Abstract. Substantial increase in the amount of civil aviation traffic and other factors have led to frequent congestion and adverse effects in terminal area. Therefore, the landing sequence of aircrafts need to be managed so as to reduce adverse effects. This type of problem is called Aircraft Landing Problem (ALP), and is an optimization problem. In this paper, the current situation of ALP research is analysed. The specific process of landing is described, and the existing research problems are classified. At the same time, on the aspect of optimization, this paper discusses the optimization processing of ALP, including the establishment of optimization model and the design of optimization algorithm. In the last, the future research trend of ALP is proposed as conclusions.

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Section: Tendencymentioning

confidence: 99%

A Review for Aircraft Landing Problem

Wang

2018

MATEC Web Conf.

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“…In recent years, for the former, a kind of fuzzy programming approach (Tavakkoli-Moghaddam et al 2012), stochastic branch and bound methods (Sölveling and Clarke 2014) and approximation algorithm (Ma et al 2014) are proposed to find an optimal or close to optimal solution. For the latter, the characteristic of the ASS problem has been analyzed from different aspects such as the arriving times (Salehipour et al 2013), runways (Hancerliogullari et al 2013;Xie et al 2013) and aircraft classes (Briskorn and Stolletz 2014;Vadlamani and Hosseini 2014). Then, the corresponding meta-heuristic approaches are introduced.…”

Section: Previous Workmentioning

confidence: 99%

“…Meanwhile, mixed-integer programming was used in this work. More recently, research on ASS has been significantly boosted by the proposal of various heuristic search methods for it, e.g., Hancerliogullari et al (2013), Salehipour et al (2013), Vadlamani and Hosseini (2014) and Xie et al (2013). Since heuristic methods are usually more flexible than mathematical programming methods, these studies have promoted ASS in terms of both problem formulation and solving.…”

Section: Introductionmentioning

confidence: 99%

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

Cao

Wei

et al. 2016

Soft Comput

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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.

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“…Dispatch rules: Hancerliogullari et al (2013) propose different dispatch rule-based and metaheuristic solution approaches. Ghoniem et al (2014) present a rule-based approach (''optimized FCFS") and a MIP-based approach (''threshold-based suboptimized heuristic").…”

Section: Solution Approachesmentioning

confidence: 99%