scholarly journals Research on Arrival/Departure Scheduling of Flights on Multirunways Based on Genetic Algorithm

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Hang Zhou ◽  
Xinxin Jiang
Keyword(s):  
Genetic Algorithm ◽  
Operating Conditions ◽  
Objective Functions ◽  
Maximum Throughput ◽  
Flight Delays ◽  
Flight Delay ◽  
Terminal Area ◽  
Optimization Scheduling

Aiming at the phenomenon of a large number of flight delays in the terminal area makes a reasonable scheduling for the approach and departure flights, which will minimize flight delay losses and improve runway utilization. This paper considered factors such as operating conditions and safety interval of multi runways; the maximum throughput and minimum flight delay losses as well as robustness were taken as objective functions; the model of optimization scheduling of approach and departure flights was established. Finally, the genetic algorithm was introduced to solve the model. The results showed that, in the program whose advance is not counted as a loss, its runway throughput is improved by 18.4%, the delay losses are reduced by 85.8%, and the robustness is increased by 20% compared with the results of FCFS (first come first served) algorithm, while, compared with the program whose advance is counted as a loss, the runway throughput is improved by 15.16%, flight delay losses are decreased by 75.64%, and the robustness is also increased by 20%. The algorithm can improve the efficiency and reduce delay losses effectively and reduce the workload of controllers, thereby improving economic results.

Design and Optimization of an Industrial Pump: Application of Genetic Algorithms and Neural Network

2005 ◽  
Author(s):  
Alain Demeulenaere ◽  
Aji Purwanto ◽  
Alban Ligout ◽  
Charles Hirsch ◽  
Ronal Dijkers ◽  
...  
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Artificial Neural Network ◽  
Large Range ◽  
Operating Conditions ◽  
Objective Functions ◽  
Design And Optimization ◽  
Integrated Environment ◽  
Mass Flows ◽  
Multipoint Optimization

This paper presents an integrated environment FINETM/Design3D developed for the optimization of turbomachinery blade shapes. The methodology relies on the interaction between a genetic algorithm, an artificial neural network, a database and user generated objective functions and constraints. The optimization is coupled to the FINETM/Turbo environment of NUMECA. The present paper focuses on the application of the multipoint optimization algorithm to the design of an industrial pump. The large range of mass flow over which the pump should operate motivates the use of multipoint optimization. The optimization exercise focuses on the efficiency, the head and the NPSH at two operating conditions characterized by largely different mass flows.

scholarly journals Multirunway Optimization Schedule of Airport Based on Improved Genetic Algorithm by Dynamical Time Window

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Hang Zhou ◽  
Xinxin Jiang
Keyword(s):  
Genetic Algorithm ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Time Window ◽  
Air Traffic ◽  
Operating Conditions ◽  
Improved Genetic Algorithm ◽  
Flight Delays ◽  
Effective Measure ◽  
Dynamical Time

Reasonable airport runway scheduling is an effective measure to alleviate air traffic congestion. This paper proposes a new model and algorithm for flight scheduling. Considering the factors such as operating conditions and flight safety interval, the runway throughput, flight delays cost, and controller workload composes a multiobjective optimization model. The genetic algorithm combined with sliding time window algorithm is used to solve the model proposed in this paper. Simulation results show that the algorithm presented in this paper gets the optimal results, the runway throughput is increased by 12.87%, the delay cost is reduced by 61.46%, and the controller workload is also significantly reduced compared with FCFS (first come first served). Meanwhile, compared with the general genetic algorithm, it also reduces the time complexity and improves real-time and work efficiency significantly. The analysis results can provide guidance for air traffic controllers to make better air traffic control.

Aerodynamic Design Optimization of an Axial Flow Compressor Stator Using Parameterized Free-Form Deformation

2019 ◽  
Vol 141 (10) ◽  
Author(s):  
Richard Amankwa Adjei ◽  
WeiZhe Wang ◽  
YingZheng Liu
Keyword(s):  
Genetic Algorithm ◽  
Flow Field ◽  
Design Optimization ◽  
Operating Conditions ◽  
Free Form ◽  
Aerodynamic Design ◽  
Objective Functions ◽  
Aerodynamic Design Optimization ◽  
Design Variables ◽  
Free Form Deformation

AbstractThis paper describes an aerodynamic design optimization of a highly loaded compressor stator blade using parameterized free-form deformation (FFD). The optimization methodology presented utilizes a B-spline-based FFD control volume to map the blade from the object space to the parametric space via transformation operations in order to perturb the blade surface. Coupled with a multi-objective genetic algorithm (MOGA) and a Gaussian process-based response surface method (RSM), a fully automated iterative loop was used to run the optimization on a fitted correlation function. A weighted average reduction of 6.1% and 36.9% in total pressure loss and exit whirl angle was achieved, showing a better compromise of objective functions with smoother blade shape than other results obtained in the open literature. Data mining of the Pareto set of optimums revealed four groups of data interactions of which some design variables were found to have skewed scatter relationship with objective functions and can be redefined for further improvement of performance. Analysis of the flow field showed that the thinning of the blade at midspan and reduction in camber distribution were responsible for the elimination of the focal-type separation vortex by redirecting the secondary flow in an axially forward direction toward the midspan and near the hub endwall downstream. Furthermore, the reduction in exit whirl angle especially at the shroud was due to the mild bow shape which generated radial forces on the flow field thereby reducing the flow diffusion rate at the suction surface corner. This effect substantially delayed or eliminated the formation of corner separation at design and off-design operating conditions. Parameterized FFD was found to have superior benefits of smooth surface generation with low number of design variables while maintaining a good compromise between objective functions when coupled with a genetic algorithm.

Optimal Control of Flight Delays Allocation at Airport

2014 ◽  
Vol 513-517 ◽  
pp. 4494-4498
Author(s):  
Zhi Wei Xing ◽  
Jiang Yu ◽  
Hong Yue Lu
Keyword(s):  
Genetic Algorithm ◽  
Optimal Control ◽  
Optimization Model ◽  
The Other ◽  
Western China ◽  
Delay Spread ◽  
Total Delay ◽  
Flight Delays ◽  
Flight Delay ◽  
Delay Allocation

Aiming at improving the unreasonable situation of flight delay allocation, an optimization model which contains two cases was proposed. One of the cases is to transfer all the delay to several delayed flights to avoid delay spread, which can increase the flight punctuality rate to ensure the departure of the majority flights. Oppositely, the other is to balance the delay losses of airlines, as well as the passengers, for realizing the fairness. According to the latest data from an airport in western China, the model was verified with genetic algorithm, which indicates that the model not only decrease the total delay losses, but also optimize the flight delay allocation which achieves the initial goal.

scholarly journals Probabilistic Flight Delay Predictions Using Machine Learning and Applications to the Flight-to-Gate Assignment Problem

Aerospace ◽  
2021 ◽  
Vol 8 (6) ◽  
pp. 152
Author(s):  
Micha Zoutendijk ◽  
Mihaela Mitici
Keyword(s):  
Assignment Problem ◽  
Absolute Error ◽  
Aviation Industry ◽  
Probabilistic Forecasting ◽  
Flight Delays ◽  
Mixture Density ◽  
Assignment Model ◽  
Gate Assignment ◽  
Flight Delay ◽  
Delay Prediction

The problem of flight delay prediction is approached most often by predicting a delay class or value. However, the aviation industry can benefit greatly from probabilistic delay predictions on an individual flight basis, as these give insight into the uncertainty of the delay predictions. Therefore, in this study, two probabilistic forecasting algorithms, Mixture Density Networks and Random Forest regression, are applied to predict flight delays at a European airport. The algorithms estimate well the distribution of arrival and departure flight delays with a Mean Absolute Error of less than 15 min. To illustrate the utility of the estimated delay distributions, we integrate these probabilistic predictions into a probabilistic flight-to-gate assignment problem. The objective of this problem is to increase the robustness of flight-to-gate assignments. Considering probabilistic delay predictions, our proposed flight-to-gate assignment model reduces the number of conflicted aircraft by up to 74% when compared to a deterministic flight-to-gate assignment model. In general, the results illustrate the utility of considering probabilistic forecasting for robust airport operations’ optimization.

scholarly journals A Method for Integration of Preferences to a Multi-Objective Evolutionary Algorithm Using Ordinal Multi-Criteria Classification

2021 ◽  
Vol 26 (2) ◽  
pp. 27
Author(s):  
Alejandro Castellanos-Alvarez ◽  
Laura Cruz-Reyes ◽  
Eduardo Fernandez ◽  
Nelson Rangel-Valdez ◽  
Claudia Gómez-Santillán ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Selective Pressure ◽  
Optimization Problems ◽  
Region Of Interest ◽  
Decision Makers ◽  
Multiple Objective ◽  
Objective Functions ◽  
Multi Objective ◽  
Imperfect Knowledge ◽  
Real World Problems

Most real-world problems require the optimization of multiple objective functions simultaneously, which can conflict with each other. The environment of these problems usually involves imprecise information derived from inaccurate measurements or the variability in decision-makers’ (DMs’) judgments and beliefs, which can lead to unsatisfactory solutions. The imperfect knowledge can be present either in objective functions, restrictions, or decision-maker’s preferences. These optimization problems have been solved using various techniques such as multi-objective evolutionary algorithms (MOEAs). This paper proposes a new MOEA called NSGA-III-P (non-nominated sorting genetic algorithm III with preferences). The main characteristic of NSGA-III-P is an ordinal multi-criteria classification method for preference integration to guide the algorithm to the region of interest given by the decision-maker’s preferences. Besides, the use of interval analysis allows the expression of preferences with imprecision. The experiments contrasted several versions of the proposed method with the original NSGA-III to analyze different selective pressure induced by the DM’s preferences. In these experiments, the algorithms solved three-objectives instances of the DTLZ problem. The obtained results showed a better approximation to the region of interest for a DM when its preferences are considered.

Development of a Hybrid Artificial Neural Network and Genetic Algorithm Model for Regime Identification of Slurry Transport in Pipelines

2009 ◽  
Vol 4 (1) ◽  
Author(s):  
Sandip K Lahiri ◽  
Kartik Chandra Ghanta
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Artificial Neural Network ◽  
Operating Conditions ◽  
Misclassification Error ◽  
Wide Range ◽  
Artificial Neural ◽  
Artificial Neural Network Ann ◽  
Pipeline Design ◽  
Hybrid Artificial Neural Network

Four distinct regimes were found existent (namely sliding bed, saltation, heterogeneous suspension and homogeneous suspension) in slurry flow in pipeline depending upon the average velocity of flow. In the literature, few numbers of correlations has been proposed for identification of these regimes in slurry pipelines. Regime identification is important for slurry pipeline design as they are the prerequisite to apply different pressure drop correlation in different regime. However, available correlations fail to predict the regime over a wide range of conditions. Based on a databank of around 800 measurements collected from the open literature, a method has been proposed to identify the regime using artificial neural network (ANN) modeling. The method incorporates hybrid artificial neural network and genetic algorithm technique (ANN-GA) for efficient tuning of ANN meta parameters. Statistical analysis showed that the proposed method has an average misclassification error of 0.03%. A comparison with selected correlations in the literature showed that the developed ANN-GA method noticeably improved prediction of regime over a wide range of operating conditions, physical properties, and pipe diameters.

Kinematic Multi-Objective Optimization of Circular-Toothed Gerotor Pumps by Genetic Algorithm

2017 ◽  
Author(s):  
Andrew J. Robison ◽  
Andrea Vacca
Keyword(s):  
Genetic Algorithm ◽  
Design Method ◽  
Third Party ◽  
Low Flow ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Generation Algorithm ◽  
Multi Objective ◽  
Pareto Curve

A gerotor gear generation algorithm has been developed that evaluates key performance objective functions to be minimized or maximized, and then an optimization algorithm is applied to determine the best design. Because of their popularity, circular-toothed gerotors are the focus of this study, and future work can extend this procedure to other gear forms. Parametric equations defining the circular-toothed gear set have been derived and implemented. Two objective functions were used in this kinematic optimization: maximize the ratio of displacement to pump radius, which is a measure of compactness, and minimize the kinematic flow ripple, which can have a negative effect on system dynamics and could be a major source of noise. Designs were constrained to ensure drivability, so the need for additional synchronization gearing is eliminated. The NSGA-II genetic algorithm was then applied to the gear generation algorithm in modeFRONTIER, a commercial software that integrates multi-objective optimization with third-party engineering software. A clear Pareto front was identified, and a multi-criteria decision-making genetic algorithm was used to select three optimal designs with varying priorities of compactness vs low flow variation. In addition, three pumps used in industry were scaled and evaluated with the gear generation algorithm for comparison. The scaled industry pumps were all close to the Pareto curve, but the optimized designs offer a slight kinematic advantage, which demonstrates the usefulness of the proposed gerotor design method.

Application of Blow-off Wind Tunnel Control Based on Genetic Algorithm Optimized BP-Neural Network PID Neural Network

2013 ◽  
Vol 310 ◽  
pp. 557-559 ◽  
Author(s):  
Li Ji ◽  
Xiao Fei Lian
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Wind Tunnel ◽  
Bp Neural Network ◽  
Control Method ◽  
Network Control ◽  
Operating Conditions ◽  
Algorithm Optimization ◽  
Large Delay ◽  
Neural Network Pid

For a blow-off tunnel running, there is the large delay and lag issues. We build a mathematical model of the wind tunnel Mach number control by the test modeling method, then analyse the pros and cons of various control methods based on BP neural network control algorithm. Put forward genetic algorithm optimization neural network adaptive control method to solve the large inertia of the wind tunnel system, and large delay. A large number of simulation studies, run a variety of operating conditions for the wind tunnel simulation proved that the improved adaptive neural network PID control method is reasonable and effective.

KOMPENSASI SEBAGAI BENTUK TANGGUNG JAWAB PIHAK MASKAPAI PENERBANGAN DALAM KETERLAMBATAN JADWAL PENERBANGAN KOMERSIAL DI INDONESIA

2019 ◽  
Vol 7 (1) ◽  
pp. 124
Author(s):  
Asmarsha Qathrinada , ◽  
Pranoto ,
Keyword(s):  
Deductive Reasoning ◽  
Legal Protection ◽  
Air Transportation ◽  
Air Transport ◽  
Flight Delays ◽  
Reasoning Patterns ◽  
The Government ◽  
Flight Delay ◽  
Secondary Materials

<p>Abstract<br />This article aims to find out how legal protection is provided to passengers in commercial air transport <br />activities in Indonesia, especially regarding airline responsibilities to passengers and the compensation <br />provided in case of flight delays due to negligence of the carrier. This research is performed with legal <br />research, using prescriptive characteristic. The research is using statute approach by reviewing the <br />regulations related to the issues. The source of the research is derived from primary legal materials namely <br />legislation, secondary materials from legal literatures, as well as tertiary or non-legal legal material. The <br />collection of legal materials was done by literature studies, and analyzed with deductive reasoning patterns. <br />Based on the result of the research, it can be concluded that the regulation of compensations given by <br />the airlines to passengers has been quite well regulated in the Minister of Transportation Regulation <br />No. 89 of 2015, but in the implementation, the government is still less firm in cracking down on airlines <br />that do not carry out their responsibility of the compensation regulated in Regulation of the Minister of <br />Transportation Number 77 in year 2011.<br />Keywords: compensation; flight delay; commercial air transportation.</p><p>Abstrak<br />Artikel ini bertujuan mengetahui bagaimana perlindungan hukum yang diberikan kepada penumpang <br />dalam kegiatan angkutan udara komersial di Indonesia, khususnya mengenai tanggung jawab maskapai <br />penerbangan terhadap penumpang serta apa kompensasi yang diberikan apabila terjadi penundaan <br />penerbangan karena kelalaian pihak pengangkut. Penelitian ini dilakukan dengan penelitian hukum dan <br />bersifat preskriptif. Pendekatan penelitian berupa pendekatan undang-undang dengan menelaah regulasi <br />yang besangkutan dengan isu yang penulis angkat dalam penulisan ini. Sumber penelitian berasal dari <br />bahan hukum primer yaitu perundang-undangan, bahan sekunder dari kepustakaan hukum, serta bahan <br />hukum tersier atau non-hukum. Pengumpulan bahan hukum dilakukan dengan studi kepustakaan, dan <br />menganalisis dengan pola penalaran deduktif.  Berdasarkan hasil penelitian maka dapat disimpulkan <br />bahwa  pengaturan  mengenai  kompensasi  yang  diberikan  oleh  maskapai  penerbangan  terhadap <br />penumpang  telah cukup  baik  diatur dalam Peraturan Menteri Perhubungan Nomor 89 Tahun 2015, <br />namun dalam pelaksanaannya pemerintah masih kurang tegas dalam menindak maskapai yang tidak <br />melaksanakan tanggung jawabnya untuk memberikan kompensasi sesuai dengan Peraturan Menteri <br />Perhubungan Nomor 77 Tahun 2011.<br />Kata kunci: kompensasi; keterlambatan penerbangan; pengangkutan udara komersial.</p>

Sign in / Sign up

Export Citation Format

Share Document