scholarly journals Optimization of Train Trip Package Operation Scheme

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Lu Tong ◽  
Lei Nie ◽  
Zhenhuan He ◽  
Huiling Fu
Keyword(s):  
Genetic Algorithm ◽  
Large Volume ◽  
High Speed ◽  
Freight Transportation ◽  
Fixed Time ◽  
Long Distance ◽  
Related Factors ◽  
Railway Freight ◽  
Proposed Model ◽  
Fixed Path

Train trip package transportation is an advanced form of railway freight transportation, realized by a specialized train which has fixed stations, fixed time, and fixed path. Train trip package transportation has lots of advantages, such as large volume, long distance, high speed, simple forms of organization, and high margin, so it has become the main way of railway freight transportation. This paper firstly analyzes the related factors of train trip package transportation from its organizational forms and characteristics. Then an optimization model for train trip package transportation is established to provide optimum operation schemes. The proposed model is solved by the genetic algorithm. At last, the paper tests the model on the basis of the data of 8 regions. The results show that the proposed method is feasible for solving operation scheme issues of train trip package.

scholarly journals Estimating the Reliability of Travel Time on Railway Networks for Freight Transportation

2018 ◽  
Vol 1 (1) ◽  
pp. 75
Author(s):  
Safoura Salehi ◽  
Abbas Mahmoudabadi
Keyword(s):  
Travel Time ◽  
Shortest Path ◽  
Freight Transportation ◽  
Travel Time Reliability ◽  
Long Distance ◽  
Rail Network ◽  
Statistical Measures ◽  
Railway Freight ◽  
Travel Time Index

<p><em>Railway freight transportation is an important transport system that its reliability causes economic issues. Freight carriers require predictable travel times to schedule their programs in competitive environment, so the estimation of reliability of travel time is very important. The present study proposes a travel time index that estimates the reliability of railway freight transportation and evaluates performance as well. Travel time reliability is estimated based on the shortest path between O-D pairs. Statistical measures of travel time, defining as the ratio of the 95th percentile travel time and the shortest path mean travel time as an ideal travel time, for each obtained route are calculated according to their selected links. Experimental data on Iranian rail network has been used as case study and results revealed that the routes less than 400 kilometers should be improved in terms of their reliabilities, because they are less reliable than long distance routes.</em><em></em></p>

scholarly journals Phase-controlled metasurface design via optimized genetic algorithm

Nanophotonics ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 3931-3939 ◽  
Author(s):  
Yulong Fan ◽  
Yunkun Xu ◽  
Meng Qiu ◽  
Wei Jin ◽  
Lei Zhang ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
High Speed ◽  
Fitness Function ◽  
Low Noise ◽  
Local Optimum ◽  
Large Area ◽  
Long Distance ◽  
Random Mutation ◽  
Light Sheet Microscopy ◽  
Optical Modes

AbstractIn an optical Pancharatnam-Berry (PB) phase metasurface, each sub-wavelength dielectric structure of varied spatial orientation can be treated as a point source with the same amplitude yet varied relative phase. In this work, we introduce an optimized genetic algorithm (GA) method for the synthesis of one-dimensional (1D) PB phase-controlled dielectric metasurfaces by seeking for optimized phase profile solutions, which differs from previously reported amplitude-controlled GA method only applicable to generate transverse optical modes with plasmonic metasurfaces. The GA–optimized phase profiles can be readily used to construct dielectric metasurfaces with improved functionalities. The loop of phase-controlled GA consists of initialization, random mutation, screened evolution, and duplication. Here random mutation is realized by changing the phase of each unit cell, and this process should be efficient to obtain enough mutations to drive the whole GA process under supervision of appropriate mutation boundary. A well-chosen fitness function ensures the right direction of screened evolution, and the duplication process guarantees an equilibrated number of generated light patterns. Importantly, we optimize the GA loop by introducing a multi-step hierarchical mutation process to break local optimum limits. We demonstrate the validity of our optimized GA method by generating longitudinal optical modes (i. e., non-diffractive light sheets) with 1D PB phase dielectric metasurfaces having non-analytical counter-intuitive phase profiles. The produced large-area, long-distance light sheets could be used for realizing high-speed, low-noise light-sheet microscopy. Additionally, a simplified 3D light pattern generated by a 2D PB phase metasurface further reveals the potential of our optimized GA method for manipulating truly 3D light fields.

scholarly journals Evaluation of Effectiveness of Different Transport Modes for Regular Mass Freight Transportation

2017 ◽  
Vol 3 (4) ◽  
pp. 204-220
Author(s):  
Sergei A Smirnov ◽  
Olga Yu Smirnova
Keyword(s):  
High Speed ◽  
Permanent Magnets ◽  
Freight Transportation ◽  
Noise Pollution ◽  
Rolling Stock ◽  
Railway Transport ◽  
Long Distance ◽  
Railway Network ◽  
Transport Modes ◽  
Mode Of Transport

The article deals with different transport modes for regular mass freight transportation, their efficiency evaluation is conducted on the bases of cost, operational and environmental properties. Introduction. Due to demand in ensuring mass transportations between Southeastern Asia and Europe, there is a topical issue of efficient application of different types of ground transport. There is a request rising, to use cutting edge achievements in technology, to increase speeds of freight transportation for long distance and their safety and environmental friendliness enhancement. Analysis. Consideration of cost properties of application of different transport modes for mass freight transportation allows revealing that the lowest infrastructure cost is typical for conventional railway transport; the lowest prime cost of transportation is ensured by maglev transport with permanent magnets of the “RosMaglev” technology; the lowest commercially profitable mode of transport for today’s level of science and technology is vacuum transport. Operationally, the leading project is “RosMaglev”, with the vacuum transport having the lowest operational efficiency. From environmental and carrying safety points of view, railway transport has gone pretty far in the recent two decades. However, a more sustainable and safe one is the maglev and vacuum modes of transport, which is explained by lack of emissions and other types of pollution, including noise pollution. In terms of safety, maglev transport is the most competitive mode of transport. Whereas, vacuum transport is the most dangerous one. Results. For mass freight transportation, the most promising mode of transport is the “RosMaglev” permanent magnets maglev transport, according to the authors. The technology allows significant increase of infrastructure construction costs. The second most promising mode is conventional railway transport. However, if the demand in transportation is low and the energy efficient traction rolling stock is implemented, the high-speed freight railway transport may be highly competitive, especially in countries with developed high-speed railway network. The vacuum transport holds firmly the third place. Conclusion. The relevance of maglev transport implementation for mass freight transportations is obvious. The maglev technologies now in use in many countries for carrying passengers have proved profitable, safe and convenient. Technical “maturity” of these technologies allows considering all points and factors when constructing maglev freight lines which is very topical due to increasing need in searching transport routes alternative to sea routes.

Railway Capacity Allocation Modeling Using a Genetic Algorithm

2017 ◽  
Vol 2608 (1) ◽  
pp. 115-124
Author(s):  
Hyunseung Kim ◽  
In-Jae Jeong ◽  
Dongjoo Park
Keyword(s):  
Genetic Algorithm ◽  
South Korea ◽  
High Speed ◽  
Rational Solution ◽  
Capacity Allocation ◽  
High Speed Railway ◽  
South Korean ◽  
Transport Services ◽  
Proposed Model ◽  
Railway Capacity

The South Korean government has established guidelines for railway capacity allocation. Railway transport services are provided by a monopoly company, which together with the guidelines, has hampered research into railway capacity allocation in South Korea. Recently, a new high-speed railway company has been established. Therefore, there is a pressing need for a fair and objective railway capacity allocation procedure. A model was developed to be applicable to South Korean high-speed railway capacity allocation, which is optimized by viewing the railway network as a location–time network. Because railway capacity allocation in South Korea is an administered process, various requirements must be followed; the model uses a genetic algorithm for such requirements. Two test scenarios were used to validate the proposed model, the solution to which resolves more than 70% of conflicts within 20 iterations (148 min). When an attempt is made to schedule infeasible trains compulsively, it is impossible to do so without relaxing one or more constraints. The average headway among real operating trains is very close to the results of the analysis. The proposed model with a genetic algorithm is a rational solution.

Crew Planning Optimization Model of High-Speed Railway

2013 ◽  
Vol 869-870 ◽  
pp. 298-304 ◽  
Author(s):  
Jin Mei Li ◽  
Lei Nie
Keyword(s):  
Genetic Algorithm ◽  
High Speed ◽  
Simulated Annealing Algorithm ◽  
Set Covering ◽  
High Speed Railway ◽  
Planning Optimization ◽  
Proposed Model ◽  
Phase Setting ◽  
Crew Planning ◽  
Covering Model

Crew planning with complicated constraints is decomposed into two sequential phases: crew scheduling phase, crew rostering phase. Setting a dynamic model based on set covering model, Genetic Algorithm is adopted based on feasible solution range in search of optimal scheduling set with minimum time. Constructing a node-arc TSP network, it adopts Genetic Algorithm and Simulated Annealing Algorithm to create a work roster. Based on Wuhan-Guangzhou High-Speed Railway in China, the balance degree of crew planning is measured by crew working time entropy. The proposed model proves strong practical application.

High-Speed, Long-Distance Electric Traction

1905 ◽  
Vol 59 (1537supp) ◽  
pp. 24627-24628
Author(s):  
Charles A. Mudge
Keyword(s):  
High Speed ◽  
Long Distance ◽  
Electric Traction

scholarly journals Modeling the Excess Velocity of Low-Viscous Taylor Droplets in Square Microchannels

Fluids ◽  
2019 ◽  
Vol 4 (3) ◽  
pp. 162 ◽  
Author(s):  
Thorben Helmers ◽  
Philip Kemper ◽  
Jorg Thöming ◽  
Ulrich Mießner
Keyword(s):  
High Speed ◽  
Process Intensification ◽  
Continuous Phase ◽  
Channel Cross Section ◽  
Optimization Approach ◽  
Mean Flow ◽  
Bypass Flow ◽  
Wall Film ◽  
Proposed Model ◽  
The Mean

Microscopic multiphase flows have gained broad interest due to their capability to transfer processes into new operational windows and achieving significant process intensification. However, the hydrodynamic behavior of Taylor droplets is not yet entirely understood. In this work, we introduce a model to determine the excess velocity of Taylor droplets in square microchannels. This velocity difference between the droplet and the total superficial velocity of the flow has a direct influence on the droplet residence time and is linked to the pressure drop. Since the droplet does not occupy the entire channel cross-section, it enables the continuous phase to bypass the droplet through the corners. A consideration of the continuity equation generally relates the excess velocity to the mean flow velocity. We base the quantification of the bypass flow on a correlation for the droplet cap deformation from its static shape. The cap deformation reveals the forces of the flowing liquids exerted onto the interface and allows estimating the local driving pressure gradient for the bypass flow. The characterizing parameters are identified as the bypass length, the wall film thickness, the viscosity ratio between both phases and the C a number. The proposed model is adapted with a stochastic, metaheuristic optimization approach based on genetic algorithms. In addition, our model was successfully verified with high-speed camera measurements and published empirical data.

Fault diagnosis of railway freight car wheelset based on deep belief network and cuckoo search algorithm

2021 ◽  
pp. 095440972110291
Author(s):  
Honghui Li ◽  
Hongkun Wang ◽  
Ziwen Xie ◽  
Mengqi He
Keyword(s):  
Fault Diagnosis ◽  
High Speed ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Deep Belief Network ◽  
Belief Network ◽  
Railway Freight ◽  
Hybrid Simulated Annealing ◽  
Technical Issues

As the key running part of the railway freight transportation system, the wheel not only bears the load of the vehicle, but also ensures the running and steering of the car body on the rails. The frequent high-speed friction with the rail and brake is the main reason for early failure of wheelset tread. Therefore, real-time status monitoring and early fault diagnosis of wheel treads have become key technical issues that must be solved in the reform of the railway freight maintenance system. In this paper, an adaptive hybrid Simulated Annealing Cuckoo Search algorithm (SA-ACS) is proposed and applied to the Deep Belief Network (DBN). The SA-ACS-DBN algorithm is used to improve the training speed and convergence accuracy of the diagnosis model. Finally, it is found through the comparison experiment of wheel tread fault data that the data results prove the feasibility of the SA-ACS-DBN model in the application of wheelset fault diagnosis.

Hierarchical Concept-Driven Language Model

2021 ◽  
Vol 15 (6) ◽  
pp. 1-22
Author(s):  
Yashen Wang ◽  
Huanhuan Zhang ◽  
Zhirun Liu ◽  
Qiang Zhou
Keyword(s):  
Language Model ◽  
Generation Process ◽  
Data Generation ◽  
Modeling Framework ◽  
Long Distance ◽  
Short Text ◽  
Proposed Model ◽  
Scalable Inference ◽  
End To End ◽  
Hidden Layer

For guiding natural language generation, many semantic-driven methods have been proposed. While clearly improving the performance of the end-to-end training task, these existing semantic-driven methods still have clear limitations: for example, (i) they only utilize shallow semantic signals (e.g., from topic models) with only a single stochastic hidden layer in their data generation process, which suffer easily from noise (especially adapted for short-text etc.) and lack of interpretation; (ii) they ignore the sentence order and document context, as they treat each document as a bag of sentences, and fail to capture the long-distance dependencies and global semantic meaning of a document. To overcome these problems, we propose a novel semantic-driven language modeling framework, which is a method to learn a Hierarchical Language Model and a Recurrent Conceptualization-enhanced Gamma Belief Network, simultaneously. For scalable inference, we develop the auto-encoding Variational Recurrent Inference, allowing efficient end-to-end training and simultaneously capturing global semantics from a text corpus. Especially, this article introduces concept information derived from high-quality lexical knowledge graph Probase, which leverages strong interpretability and anti-nose capability for the proposed model. Moreover, the proposed model captures not only intra-sentence word dependencies, but also temporal transitions between sentences and inter-sentence concept dependence. Experiments conducted on several NLP tasks validate the superiority of the proposed approach, which could effectively infer meaningful hierarchical concept structure of document and hierarchical multi-scale structures of sequences, even compared with latest state-of-the-art Transformer-based models.

scholarly journals A new evaluation and prediction model of sound quality of high-speed permanent magnet motor based on genetic algorithm-radial basis function artificial neural network

2021 ◽  
Vol 104 (3) ◽  
pp. 003685042110311
Author(s):  
Kai Hu ◽  
Guangming Zhang ◽  
Wenyi Zhang
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Artificial Neural Network ◽  
Basis Function ◽  
High Speed ◽  
Objective Evaluation ◽  
Sound Quality ◽  
Average Error ◽  
Permanent Magnet Motor ◽  
Predicted Model

Sound quality (SQ) has become an important index to measure the competitiveness of motor products. To better evaluate and optimize SQ, a novelty SQ evaluation and prediction model of high-speed permanent magnet motor (HSPMM) with better accuracy is presented in this research. Six psychoacoustic parameters of A-weighted sound pressure level (ASPL), loudness, sharpness, roughness, fluctuation strength (FS), and perferred-frequency speech interference (PSIL) were adopted to objectively evaluate the SQ of HSPMM under multiple operating conditions and subjective evaluation was also conducted by the combination of semantic subdivision method and grade scoring method. The evaluation results show that the SQ is poor, which will have a certain impact on human psychology and physiology. The correlation between the objective evaluation parameters and the subjective scores is analyzed by coupling the subjective and objective evaluation results. The average error of multiple linear regression (MLR) model is 7.10%. It has good accuracy, but poor stability. In order to improve prediction accuracy, a new predicted model of radial basis function (RBF) artificial neural network was put forward based on genetic algorithm (GA) optimization. Compared with MLR, its average error rate is reduced by 3.16% and the standard deviation is reduced by 1.841. In addition, the weight of each objective parameter was analyzed. The new predicted model has a better accuracy. It can evaluate and optimize the SQ exactly. The research methods and conclusions of this paper can be extended to the evaluation, prediction, and optimization of SQ of other motors.

Sign in / Sign up

Export Citation Format

Share Document