• Journal of the Korean Society for Railway
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• v.19 no.2
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• pp.234-242
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• 2016

In express operation plans for urban trains, it is effective for the reduction of the number of sidetracks to apply a high performance train that has improved acceleration/deceleration ability and a regular train to local and express trains, respectively. In this research, based on a plan to use a high performance train for a local train, an optimization methodology is suggested to reduce the number of sidetracks and the operation time of the local train simultaneously. The optimization solver applied in this research is a genetic algorithm; headway, location of sidetrack and waiting time at the sidetrack are considered as design variables in the optimization problem. Consequently, by applying this system to Seoul metro line no.7, the effect of the suggested methodology was verified by obtaining the proper optimum solution.

• Proceedings of the Safety Management and Science Conference
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• 2003.05a
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• pp.53-61
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• 2003

The process of railway traffic planning is composed of several steps such as long - term, mid - term, short - term, and real - time plan. The planning of vehicle and manpower resources is a main research topic in tactical short - term planning step Railway vehicle is usually consisted of a power car, passenger/freight cars and human resource is composed of engine driver, cabin crew, ground personnel. So far , power car was main research target in railway vehicle scheduling problem. Recently according as the light electric railway or high - speed railway is introduced, the operational planning of train set vehicles become important . In this paper , we introduce the conceptional model for trainset restoring problem and developed heuristic algorithm.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.1359-1370
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• 2008

In the track geometry such as rails, sleepers, ballasts and fastener, track deterioration occurs by repetitive train weight and the high-speed railway takes a trend faster than normal. Track deterioration of over threshold value harms ride comfort and furthermore affect in trains safety seriously. An organic and systematic track maintenance system is very important because a trend of the track deterioration effects on track life-cycle and running safety. Also costs of the railway track permanent way and its maintenance are extremely large, forming a significant part of the total infrastructure expenditure. Therefor reasonable and efficient track maintenance has to be planed on a budget. It is required to carry out not only corrective maintenance but preventive maintenance for the track maintenance. In order to perform maintenance jobs in the boundary of the machines and resources given regarding the type and amount jobs, it is necessary to determine feasible or optimal scheduling considering the priority. In this study, the system organization and required functions for the development of track maintenance system supported track deterioration prediction and optimal scheduling are proposed.

• Journal of the Korean Society of Systems Engineering
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• v.10 no.2
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• pp.43-50
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• 2014

The Centralized Traffic Control(CTC) System of Urban Railway is an element(subsystem) of the Urban Railway system to aim safety operation and efficient management of rolling stock in accordance with a train scheduling program in train operation ways. That's why the CTC System must be developed considering systematic and safety-guaranteed methods such as RAMS(Reliability, Availability, Maintainability, and Safety) refereed to IEC standards. The CTC System is consists of rolling stock, signaling, power supply, communication, and mechanical equipment and preforms control and remote monitoring functions. The technical activities considering safety process are very important at such an early stage of development in a railway project. This paper introduces RAMS activities and an independent safety assessment by $3^{rd}$ Party focused on a safety applied to a development of the CTC system of Urban Railway and proposes the experiences as well practices.

• Proceedings of the KSR Conference
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• 2007.05a
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• pp.1481-1498
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• 2007

As railroad industry face the new Renaissance era, effective and efficient maintenance methods for rolling stock operation are required with advanced railroad technology. All kinds of railroad systems such as high speed long distance train, metropolitan mass transit and light rail require systematic maintenance technology in order to maintain the safe railroad operation. Simulation models for detailed operations of the sample maintenance center are developed. In this study, standard maintenance procedures, layout, equipments and number of workers of Siheung Metropolitan Railroad Maintenance Rolling Stock Depot are considered. The proposed simulation models are developed using simulation package ARENA. Three simulation analysis using the developed simulation model are done. First, the bottleneck operation is identified. Second, the relationship between maintenance center size, number of workers and cycle time is analyzed. Lastly, the scheduling performances between PERT/CPM and Critical Chain Project Management(CCPM) are compared.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.1441-1446
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• 2008

Seoul Metro Line 9 (SML9) is the first subway line that private capital invests in Korea. SML9 will cross Seoul, linking the Gimpo Airport to the Gangnam district (25.5km) opening in the first half of 2009. SML9 has a new model in Korea constructed by metropolitan government and private company and operated by specialized public transportation service provider. SML9 is confronted with tough environment of stagnated public transportation and strong competitor, Olympic city expressway. And SML9 is under pressure for showing high efficiency as non-governmental organization from both customers and government. Consequently SML9 must lead the maximum efficiency by using its material and human resource. It is necessary that SML9 raise a competitive power and display its ability in active collaboration with relative organization and company. Hereupon, I propose renovation plans from viewpoint of operation field of SML9, (1) efficient train scheduling regime focusing on the combination of express and local train (2) close connection of other mean of transportation and (3) effective connection convention with Airport Railroad (AREX) as the line connected directly.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06a
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• pp.290-293
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• 2011

현재 전국적으로 도시 철도의 각 호선별 열차 운행은 차량기지에서 출고된 열차가 기점과 종점의 두 지점 사이를 여러 차례 왕복한 후 정해진 차량기지로 입고방식을 취하는 것이 대부분이다. 그리고 매일 열차 운행이 개시되기 전 각 차량기지의 보유 열차 수는 전날과 동일해야 하는데 차량 기지가 복수로 존재할 경우 열차 운행계획 수립 시 어느 기지에서 출고한 어떤 차량이 어느 기지로 입고해야 하는지를 결정하는 문제가 더욱 어려워진다. 승객 수송을 위한 여러 가지 요구조건 또한 모두 만족시키면서 이 입출고 제약도 만족시키는 것은 쉬운 문제가 아니다. 하지만 열차 운행 계획 수립을 자동으로 생성하는 방법에 대한 연구는 매우 부족한 실정이다. 따라서 본 논문에서는 차량기지가 복수로 존재하는 상황에서의 현실 제약을 모두 만족하는 도시철도 운행 계획을 자동으로 생성하는 방법을 제시한다. 본 논문에서 제시하는 방법으로 실험 한 결과 기존의 방법으로 해결이 어려운 차량기지가 복수로 존재하는 상황에서의 현실제약을 모두 만족하는 계획을 빠른 시간 내에 수립 할 수 있음을 확인 하였다.

• Journal of Korean Society of Transportation
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• v.8 no.2
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• pp.67-75
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• 1990

This paper treats the problem to schedule for trains with how transit priority so as to maximizing the number that can be sent during given time periods without interfering with the fixed schedule for train with high transit priority in a track. We transform the this problem into Time Expanded Network without traverse time through application of Ford and Fulkerson Model and construct the Enumeration Algorithm for solutions using TENET Generator (TENETGEN). Finally, we compare our algorithm with Dinic's Maximal-Flow Algorithm and examine the avaliability of our procedures in personal computer.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.6
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• pp.3851-3857
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• 2014

Shippers' requests of freight trains vary with time, but generating an additional schedule of freight trains is not easy due to many considerations, such as the line capacity, operation rules, and conflicts with existing trains. On the other hand, an additional freight train schedule has been continuously requested and manually processed by domestic train operation companies using empirical method, which is time consuming. This paper proposes a model to determine the additional freight train schedule that assesses the feasibility of the added freight trains, and generates as many additional schedules as possible, while minimizing the delay of the existing schedules. The problem is presented using time-space network, modeled as multi-commodity flow problem, and solved using the column generation method. Three levels of experiment were conducted to show validity of the proposed model in the computation time.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.374-388
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• 2022

Cloud computing has been one of the most critical technology in the last few decades. It has been invented for several purposes as an example meeting the user requirements and is to satisfy the needs of the user in simple ways. Since cloud computing has been invented, it had followed the traditional approaches in elasticity, which is the key characteristic of cloud computing. Elasticity is that feature in cloud computing which is seeking to meet the needs of the user's with no interruption at run time. There are traditional approaches to do elasticity which have been conducted for several years and have been done with different modelling of mathematical. Even though mathematical modellings have done a forward step in meeting the user's needs, there is still a lack in the optimisation of elasticity. To optimise the elasticity in the cloud, it could be better to benefit of Machine Learning algorithms to predict upcoming workloads and assign them to the scheduling algorithm which would achieve an excellent provision of the cloud services and would improve the Quality of Service (QoS) and save power consumption. Therefore, this paper aims to investigate the use of machine learning techniques in order to predict the workload of Physical Hosts (PH) on the cloud and their energy consumption. The environment of the cloud will be the school of computing cloud testbed (SoC) which will host the experiments. The experiments will take on real applications with different behaviours, by changing workloads over time. The results of the experiments demonstrate that our machine learning techniques used in scheduling algorithm is able to predict the workload of physical hosts (CPU utilisation) and that would contribute to reducing power consumption by scheduling the upcoming virtual machines to the lowest CPU utilisation in the environment of physical hosts. Additionally, there are a number of tools, which are used and explored in this paper, such as the WEKA tool to train the real data to explore Machine learning algorithms and the Zabbix tool to monitor the power consumption before and after scheduling the virtual machines to physical hosts. Moreover, the methodology of the paper is the agile approach that helps us in achieving our solution and managing our paper effectively.