scholarly journals Stochastic Runway Scheduling Problem With Partial Distribution Information of Random Parameters

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 68460-68473
Author(s):  
Ming Liu ◽  
Bian Liang ◽  
Maoran Zhu ◽  
Chengbin Chu
Keyword(s):  
Scheduling Problem ◽  
Random Parameters ◽  
Partial Distribution ◽  
Runway Scheduling

scholarly journals Time-Indexed Formulations for the Runway Scheduling Problem

2017 ◽  
Vol 51 (4) ◽  
pp. 1196-1209 ◽  
Author(s):  
Pasquale Avella ◽  
Maurizio Boccia ◽  
Carlo Mannino ◽  
Igor Vasilyev
Keyword(s):  
Scheduling Problem ◽  
Runway Scheduling

A branch and cut heuristic for a runway scheduling problem

2016 ◽  
Vol 77 (11) ◽  
pp. 1985-1993 ◽  
Author(s):  
I. L. Vasilyev ◽  
P. Avella ◽  
M. Boccia
Keyword(s):  
Branch And Cut ◽  
Scheduling Problem ◽  
Runway Scheduling

scholarly journals An Efficient Approximation Algorithm for Aircraft Arrival Sequencing and Scheduling Problem

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Weimin Ma ◽  
Bo Xu ◽  
Ming Liu ◽  
Hui Huang
Keyword(s):  
Approximation Algorithm ◽  
Numerical Study ◽  
Scheduling Problem ◽  
Np Hard ◽  
Scheduling System ◽  
Efficient Approximation Algorithm ◽  
Sequencing And Scheduling ◽  
Permutation Problem ◽  
Efficient Approximation ◽  
Runway Scheduling

The aircraft arrival sequencing and scheduling (ASS) problem is a salient problem in airports' runway scheduling system, which proves to be nondeterministic polynomial (NP) hard. This paper formulates the ASS in the form of a constrained permutation problem and designs a new approximation algorithm to solve it. Then the numerical study is conducted, which validates that this new algorithm has much better performance than ant colony (AC) algorithm and CPLEX, especially when the aircraft types are not too many. In the end, some conclusions are summarized.

scholarly journals The aircraft runway scheduling problem: A survey

2021 ◽  
Vol 132 ◽  
pp. 105336
Author(s):  
Sana Ikli ◽  
Catherine Mancel ◽  
Marcel Mongeau ◽  
Xavier Olive ◽  
Emmanuel Rachelson
Keyword(s):  
Scheduling Problem ◽  
Runway Scheduling

Optimal broadcast scheduling method for VANETs: An adaptive discrete firefly approach

2020 ◽  
Vol 39 (6) ◽  
pp. 8125-8137
Author(s):  
Jackson J Christy ◽  
D Rekha ◽  
V Vijayakumar ◽  
Glaucio H.S. Carvalho
Keyword(s):  
Intelligent Transportation System ◽  
Search Algorithm ◽  
Mac Protocol ◽  
High Mobility ◽  
Optimal Solution ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Traffic Density ◽  
Scheduling Problem ◽  
Broadcast Scheduling

Vehicular Adhoc Networks (VANET) are thought-about as a mainstay in Intelligent Transportation System (ITS). For an efficient vehicular Adhoc network, broadcasting i.e. sharing a safety related message across all vehicles and infrastructure throughout the network is pivotal. Hence an efficient TDMA based MAC protocol for VANETs would serve the purpose of broadcast scheduling. At the same time, high mobility, influential traffic density, and an altering network topology makes it strenuous to form an efficient broadcast schedule. In this paper an evolutionary approach has been chosen to solve the broadcast scheduling problem in VANETs. The paper focusses on identifying an optimal solution with minimal TDMA frames and increased transmissions. These two parameters are the converging factor for the evolutionary algorithms employed. The proposed approach uses an Adaptive Discrete Firefly Algorithm (ADFA) for solving the Broadcast Scheduling Problem (BSP). The results are compared with traditional evolutionary approaches such as Genetic Algorithm and Cuckoo search algorithm. A mathematical analysis to find the probability of achieving a time slot is done using Markov Chain analysis.

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