• Management Science and Financial Engineering
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• v.10 no.1
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• pp.53-75
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• 2004

Most existing studies on time-dependent networks have been focused on finding a minimum delay path given a departure time at the origin. There, however, frequently happens a situation where users can select any departure time in a certain time interval and want to spend as little time as possible on traveling the networks. In that case. the delay spent on traveling networks depends on not only paths but also the actual departure time at the origin. In this paper, we propose a new problem in time-dependent networks whose objective is to find an optimal departure time given possible departure time interval at the origin. From the optimal departure time, we can obtain a path with minimum delay among all paths for possible departure times at the origin. In addition, we present an algorithm for finding an optimal departure time by enumerating trees which remain shortest path tree for a certain time interval.

• Journal of Korean Society for Quality Management
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• v.38 no.2
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• pp.171-179
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• 2010

Pearn et al.(2002) supposed the $C_{pp}$ multiple process performance analysis chart. This chart displays multiple processes with the process variation and process departure on one single chart. But, this chart can not display the distribution of the process variation and process departure and is inappropriate for processes with non-normal distributions. With bootstrapping method, we can display the distribution of the process variation and process departure on the $C_{pp}$ multiple process performance analysis chart.

• Journal of Advanced Navigation Technology
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• v.24 no.6
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• pp.515-520
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• 2020

The development of autopilot system and flight management system (FMS) equipment in today's aircraft navigation can be attributed to the reduction of pilots' workload and the navigation safety. The effect of autopilot and FMS equipment is greater, especially in heavy airport traffic or complicated of the departure. However, some airport specific departure procedures result in an uncommanded turn event due to an error in the FMS, causing aircraft to deviate from the center line of the route. With most departure procedures requiring area navigation (RNAV) operation, pilot situation awareness and corrective action are the only ways to minimize aircraft deviation to maintain the safety of area navigation. Through analysis of the occurrence status of the uncommended turn event by aircraft type, airport and flight phase, and comparative analysis of the survey results of foreign airlines and the airlines self-reduction plan with the aircraft manufacturer's corrective action, it is intended to give implications for the need for more fundamental measures to prevent recurrence of such events.

• Proceedings of the Korean Society for Quality Management Conference
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• 2007.04a
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• pp.287-296
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• 2007

Pearn et al.(2002) supposed the $C_{pp}$ multiple process performance analysis chart. This chart display multiple processes with the process variation and process departure on one single chart. But, this chart can not display the distribution of the process variation and process departure. With bootstrapping method, we can display the distribution of the process variation and process departure on the $C_{pp}$ multiple process performance analysis chart.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.26 no.2
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• pp.39-46
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• 2018

Departure Manager (DMAN) is a tool to optimize the departure sequence and to suggest appropriate take-off time and off-block time of each departure aircraft to the air traffic controllers. To that end, Variable Taxi Time (VTT), which is time duration of the aircraft from the stand to the runway, should be estimated. In this paper, a study for development of VTT prediction algorithm based on machine learning techniques is presented. The factors affecting aircraft taxi speeds were identified through the analysis of historical traffic data on the airport surface. The prediction model suggested in this study consists of several sub-models that reflect different types of surface maneuvers based on the analysis result. The prediction performance of the proposed method was evaluated using the actual operational data.

• Journal of Industrial Technology
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• v.37 no.1
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• pp.5-11
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• 2017

The purpose of this research is to propose an efficient loop line operation plan for customer transportation in a new theme park. Based on the expected customer arrivals, customer loading/unloading methods, and scheduled/non-scheduled departure schemes, movement time between stations etc., we have performed indepth analyses and derived the best optimal policy. Our results show that, over all, the operation with separate loading/unloading doors and scheduled departure is preferred to the other options. We then derived the optimal number of trains and cars meeting minimal customer unsatisfaction with low cost for each season.

• Journal of the Korea Convergence Society
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• v.9 no.5
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• pp.7-14
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• 2018

The purpose of this study is to analyze the effect of commuter's departure time on transportation system in future traffic system operated autonomous vehicle using agent based model. Various scenarios have been set up, such as when all passenger choose a similar departure time, or if the passenger chooses a different departure time. Also, this study tried to analyze the effect of road capacity. It was found that although many of the scenarios had been completed in a stable manner, many commuters were significantly coordinated at the desired departure time. In particular, in the case of a reduction in road capacity or in certain scenarios, it has been shown that, despite excessive schedule adjustments, many passengers are unable to commute before 9 o'clock. As a result, it is suggested that traffic management and pricing policies are different from current ones in the era of autonomous car operation.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.24 no.4
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• pp.44-52
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• 2016

The departure flow management is the planning tool to optimize the schedule of the departure aircraft and allows them to join smoothly into the overhead traffic flow. To that end, the arrival time prediction to the merge point for the cruising aircraft is necessary to determined. This paper proposes a trajectory prediction model for the cruising aircraft based on the machine learning approach. The proposed method includes the trajectory vectored from the procedural route and is applied to the historical data to evaluate the prediction performances.

• Industrial Engineering and Management Systems
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• v.1 no.1
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• pp.29-45
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• 2002

In this study, we consider infinite supply of raw materials and backlogged demands as given two boundary conditions. And we need not make any specific assumptions about the inter-arrival of external demand and service time distributions. We propose a numeric model and an algorithm in order to compute the first two moments of inter-departure process. Entropy enables us to examine the convergence of this process and to derive measurable relations of this process. Also, lower bound on the variance of inter-departure process plays an important role in proving the existence and uniqueness of an optimal solution for a numeric model and deriving the convergence order of augmented Lagrange multipliers method applied to a numeric model. Through these works, we confirm some structural properties and numeric examples how the validity and applicability of our study.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.97-99
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• 2011

본 논문에서는 안전주행지원 솔루션인 스마트폰용 차선이탈경보 애플리케이션의 실행 속도 향상 방법을 연구하였다. 이전 연구에서 스마트폰(iPhone 3GS) 기반의 차선이탈경보 어플리케이션을 개발하였는데 입력 영상의 처리 속도가 1.52fps였다. 본 연구에서는 영상 처리 속도를 향상시키기 위한 최적화 작업을 진행하였으며 기존의 차선이탈경보 어플리케이션의 차선인식 속도보다 프레임당 평균 0.4초 정도 단축되어 약 4fps 속도로 성능을 보였다. 향후 추가 연구를 통해 처리 속도를 좀 더 향상시킬 것이다.