• Proceedings of the Society of Korea Industrial and System Engineering Conference
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• 2002.05a
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• pp.99-104
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• 2002

This paper addresses a problem of machining route selection and determination of input quantity with yield in multi-stage flexible flow system. The problem is formulated as nonlinear programing and the proposed model is solved by genetic algorithm(GA) approach. The effectiveness of the proposed GA approach is evaluated through comparisons with the optimal solution obtained from the branch and bound for the same problem.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.400-403
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• 2021

Algorithms for predicting the optimal route of vehicles are being actively sudied with the recent development of autonomous driving technology. Companies such as SK, Kakao, and Naver provide services that navigate the optimal route. They predicts the optimal path with information from the users in real time. However, they can predict the optimal route, but not optimal lane route. We proposes a system that navigates the optimal lane path with coordinates data from vehicles using Lidar sensor. The proposed method is a system that guides smooth lanes by acquiring time series coordinate data of a vehicle after performing the Lidar-based object detection method. we demonstrates the performance using actual acquired data from the experimental results.

• CDE review
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• v.21 no.2
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• pp.34-38
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• 2015

In case of the big city, choosing the adequate root of which we can reach the destination can affect the driver's condition and driving time. so it is quite important to find the optimal routes for arriving the destination as considering the factors, such as driving conditions or travel time and so on. In this paper, we develop route choice model with considering driving conditions and travel time, and it can search the optimal path which make drivers reduce their fatigues using genetic algorithm.

• Journal of Korean Society of Transportation
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• v.5 no.1
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• pp.3-23
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• 1987

Traffic signal control problems in urban street networks are formulated in two ways. In the formulations network flows are assumed to satisfy the user route choice criterion. the first formulation which is called implicit substiuation incorporates user route behavior implicitly in the objective function by recognizing the dependence of the link flows on the signal variables. On the other hands, the second one which is called 'penalty formulation' consists in expressing the route choice conditions in the form of a single nonlinear constraint. Approximate solution algorithm for each of the formulations was investigated in detail and computer codes were written to examine key aspects of each algorithm. A test was done on a network which is small in size but sufficiently complex in representing real-world traffic conditions and the test result shows that both algorithms produce converged solutions. It is recommended, however, that further studies should be done in order to compare the performance of each algorithm more in depth.

• Journal of Aerospace System Engineering
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• v.14 no.6
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• pp.1-9
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• 2020

Global e-commerce and delivery companies are actively pursuing last-mile delivery service using drones, and various delivery schedule planning studies have been conducted. In this study, separate individual route networks were constructed to reflect drone route constraints such as prohibited airspace and truck route constraints such as rivers, which previous studies did not incorporate. The A* algorithm was used to calculate the shortest path distance matrix between the starting point and destinations. In addition, we proposed an optimal delivery schedule plan using genetic algorithms and applied it to compare the efficiency with that of vehicle-only delivery.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.100-103
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• 2023

Recently, development of maritime autonomoust surface ships and eco-friendly ships, production and evaluation research considering various marine environments is needed in the field of optimal routes as the demand for accurate and detailed real-time marine environment prediction information expands. An algorithm that can calculate the optimal route while reducing the risk of the marine environment and uncertainty in energy consumption in smart ships was developed in 2 stages. In the first stage, a profile was created by combining marine environmental information with ship location and status information within the Automatic Ship Identification System(AIS). In the second stage, a model was developed that could define the marine environment energy map using the configured profile results, A regression equation was generated by applying Random Forest among machine learning techniques to reflect about 600,000 data. The Random Forest coefficient of determination (R²) was 0.89, showing very high reliability. The Dijikstra shortest path algorithm was applied to the marine environment prediction at June 1 to 3, 2021, and to calculate the optimal safety route and express it on the map. The route calculated by the random forest regression model was streamlined, and the route was derived considering the state of the marine environment prediction information. The concept of route calculation based on real-time marine environment prediction information in this study is expected to be able to calculate a realistic and safe route that reflects the movement tendency of ships, and to be expanded to a range of economic, safety, and eco-friendliness evaluation models in the future.

• Journal of the Korean Society for Railway
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• v.18 no.2
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• pp.149-156
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• 2015

It is necessary to determine real path for urban railway users in order to allocate revenues between urban railway organizations. Out of several algorithms used to determine optimal routes, the k-path algorithm based on link-label has been utilized. However, this k-path algorithm has certain flaws. For example, optimal route can change depending on the travel and walking time, transfer penalty, and so on. Also, this algorithm cannot take into account the characteristics of users, who prefer express train to normal trains. In this paper, an algorithm is proposed to determine one single optimal route based on the traffic card data. This method also can search for an optimal path in conjunction with the railway timetable.

• ETRI Journal
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• v.27 no.6
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• pp.733-746
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• 2005

In the context of multi-protocol label switching (MPLS) traffic engineering, this paper proposes a scalable constraintbased shortest path first (CSPF) routing algorithm with multiple QoS metrics. This algorithm, called the multiple constraint-based shortest path first (M_CSPF) algorithm, provides an optimal route for setting up a label switched path (LSP) that meets bandwidth and end-to-end delay constraints. In order to maximize the LSP accommodation probability, we propose a link weight computation algorithm to assign the link weight while taking into account the future traffic load and link interference and adopting the concept of a critical link from the minimum interference routing algorithm. In addition, we propose a bounded order assignment algorithm (BOAA) that assigns the appropriate order to the node and link, taking into account the delay constraint and hop count. In particular, BOAA is designed to achieve fast LSP route computation by pruning any portion of the network topology that exceeds the end-to-end delay constraint in the process of traversing the network topology. To clarify the M_CSPF and the existing CSPF routing algorithms, this paper evaluates them from the perspectives of network resource utilization efficiency, end-to-end quality, LSP rejection probability, and LSP route computation performance under various network topologies and conditions.

• Korean Management Science Review
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• v.17 no.2
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• pp.55-65
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• 2000

This paper addresses a problem of machining route selection in multi-stage process with machine group. This problem is considered the subcontracting and the production in-house such as regular and overtime work. the proposed model is formulated as a 0-1 integer programming constraining the avaliable time of each machine for planning period and total overtimes. The objective of the model is to minimize the sum of processing cost, overtime cost, and subcontracting cost. To solve this model, a genetic algorithm(GA) approach is developed. The effectiveness of the proposed GA approach is evaluated through comparisons with the optimal solution obtained from the branch and bound. In results, the same optimal solution is obtained from two methods at small size problem, and the consistent solution is provided by the GA approach at large size problem. The advantage of the GA approach is the flexibility into decision-making process because of providing multiple machining routes.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.7
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• pp.1159-1164
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• 2004

There is an Overhead Hoist Transport(OHT) for delivering the wafer in semiconductor processing. The transfer system is consists of carrier vehicle. rail, and support. OHTCMS(OHT Control and Management System) has to take the feature, such as the optimal control and integration with several OHT. In this paper, ESRA(Efficiency of Shortest - Route Algorithms) is proposed which can be transported optimal route and be prevented collision using the Floyd-Warshall algorithms. The proposed algorithm is verified through consecutive simulation for a long time.