• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2007.12a
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• pp.226-227
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• 2007

Significant increase of container flows in marine terminals requires more efficient automatic port systems. This paper presents a novel routing and collision avoidance algorithm of linear motor based shuttle cars using random access sequence dynamic programming (RAS DP). The proposed RAS DP is accomplished online for determining optimal paths for each shuttle car.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.10
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• pp.59-70
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• 1997

Until now, considerable progress has been made in the application of range finding techanique performing direct 3-D measurement from the object. However, ther are few use of the method in the area of the application of material handing. We present a range finding vision system consisting of static and dynamic range finders to automate a reclaimer used for material handling. A static range finder detects range data of the front part of the piles of material, and a height map is obtained from the proposed image processing algorithm. The height map is used to calculate the optimal job path as features for required information for material handling function. A dynamic range finder attached on the side of the arm of the reclaimer detects the change of the local properties of the material with the handling function, which is used for avoiding collision and detecting the ending point for changing direction. the developed vision systm was applied to a 1/20 simulator and the results of test show that it is appropriate to use for automating the material handling.

• The KIPS Transactions:PartB
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• v.12B no.3 s.99
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• pp.313-322
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• 2005

In order to access digital items in a server via ubiquitous devices, the digital items should be adapted according to the system environment, device characteristics and user preferences. In ubiquitous environment, those device-dependent adaptation requirements are not statically determined and not predictable. Therefore an application specific adaptation mechanism can not be applied to a general digital item adaptation engine. In this paper, we propose an application independent digital item adaptation architecture which has a set of minimal transcoders, transcoding path generator for a required adaptation requirement, and adaptation scheduler. And a CFG based method of finding a sequence of multiple unit transcoders called a transcoding path Is described in detail followed by experimental results.

• Journal of Korean Society of Transportation
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• v.26 no.1
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• pp.127-135
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• 2008

Generally, optimum shortest path algorithms adopt single attribute objective among several attributes such as travel time, travel cost, travel fare and travel distance. On the other hand, multi-objective shortest path algorithms find the shortest paths in consideration with multi-objectives. Up to recently, the most of all researches about multi-objective shortest paths are proceeded only in single transportation mode networks. Although, there are some papers about multi-objective shortest paths with multi-modal transportation networks, they did not consider transfer problems in the optimal solution level. In particular, dynamic programming method was not dealt in multi-objective shortest path problems in multi-modal transportation networks. In this study, we propose a multi-objective shortest path algorithm including dynamic programming in order to find optimal solution in multi-modal transportation networks. That algorithm is based on two-objective node-based label correcting algorithm proposed by Skriver and Andersen in 2000 and transfer can be reflected without network expansion in this paper. In addition, we use non-dominated paths and tree sets as labels in order to improve effectiveness of searching non-dominated paths. We also classifies path finding attributes into transfer and link travel attribute in limited transit networks. Lastly, the calculation process of proposed algorithm is checked by computer programming in a small-scaled multi-modal transportation network.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.03a
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• pp.123-126
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• 1998

The theoretical foundations of GA are the Schema Theorem and the Building Block Hypothesis. In the Meaning of these foundational concepts, simple genetic algorithm(SGA) allocate more trials to the schemata whose average fitness remains above average. Although SGA does well in many applications as an optimization method, still it does not guarantee the convergence of a global optimum. Therefore as an alternative scheme, there is a growing interest in a co-evolutionary system, where two populations constantly interact and co-evolve in contrast with traditional single population evolutionary algorithms. In this paper, we propose a new design method of an optimal fuzzy logic controller using co-evolutionary concept. In general, it is very difficult to find optimal fuzzy rules by experience when the input and/or output variables are going to increase. So we propose a co-evolutionary method finding optimal fuzzy rules. Our algorithm is that after constructing two population groups m de up of rule vase and its schema, by co-evolving these two populations, we find optimal fuzzy logic controller. By applying the proposed method to a path planning problem of autonomous mobile robots when moving objects exist, we show the validity of the proposed method.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.1
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• pp.17-25
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• 2011

At the computer games, we can experience a variety of environments using a virtual object. It is similar to that be trained in War-game simulator of the defense. Actual soldiers and a computer-generated virtual group(Computer Generated Force: CGF) in 3-D virtual battlefield environment are training. However, path finding algorithm, one of the techniques of simulation models, to the current level only considers the shortest time path. So, this current level at the special situation of the army in the battlefield for selecting the optimal path is limited. The focus of this paper is to select the least-cost path using the deadline with several different mission conditions(METT+TC). For the only shortest time path algorithm and the least-cost path algorithm using dealine,($d_t$, one of METT+TC elements), Its usefulness is verifying the change of the move spent time(t) for all possible paths and the fighting power of the combat troops(Troops ability, a) through a comparison of the total cost of moves(c(t)). According to the results, when considering the deadline, the proposed algorithm saves about 62.5% of the maximum cost.

• Journal of Korean Society of Transportation
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• v.24 no.5 s.91
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• pp.77-88
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• 2006

The purpose of this study is to Propose the time dependent K-least time path algorithm applicable to a real-time based operation strategy in multi-modal transportation network. For this purpose, we developed the extended method based on entire path deletion method which was used in the static K-least time path algorithm. This method was applied to time dependent K-least time path algorithm to find k least time paths in order based on both time dependant mode-link travel time and transfer cost In particular, this algorithm find the optimal solution, easily describing transfer behavior, such as walking and waiting for transfer by applying a link-based time dependent label. Finally, we examined the verification and application of the Proposed algorithm through case study.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.1
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• pp.10-21
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• 2008

User travel behavior is based on the existence of complete traffic information in deterministic user optimal principle by Wardrop(1952). According to deterministic user optimal principle, users choose the optimal route from origin to destination and they change their routes arbitrarily in order to minimize travel cost. In this principle, users only consider travel time as a factor to take their routes. However, user behavior is not determined by only travel time in actuality. Namely, the models that reflect only travel time as a route choice factor could give irrational travel behavior results. Therefore, the model is necessary that considers various factors including travel time, transportation networks structure and traffic information. In this research, more realistic deterministic optimal traffic assignment model is proposed in the way of route recognizance behavior. This model assumes that when users decide their routes, they consider many factors such as travel time, road condition and traffic information. In addition, route recognizance attributes is reflected in this suggested model by forward searching method and backward searching method with numerical formulas and algorithms.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.9
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• pp.82-87
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• 2008

Faster, safer and cheaper mailing of the postal matter is essential for surviving in the competitive market of home-delivery service. In the past, the domestic delivery business has been nu by only a few number of companies. But more and more number of companies including medium size ones are participating in the business, and the competition is getting severe. This paper proposes a method to select the optimal location of mail distribution centers that minimally connect the local mail centers of some major cities in Korea using the Steiner Tree theory, which is about connecting a finite number of points with a minimal length of paths and has been used in the distribution system optimization and optimal routing of the transmission lines of the electric power system. By using Steiner Tree theory in finding the best location of the postal delivery hub, we may expect the reduction of transportation cost and the increase of profit, resulting in acquiring the superior position in the competitive delivery business. It is expected that we may use the Steiner Tree theory in finding the best location of the electric power substation for the nott higher EHV(extreme high voltage) transmission network.

• Journal of Internet Computing and Services
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• v.11 no.1
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• pp.103-116
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• 2010

In this paper, we propose an optimal camera placement using agent-based simulation. To derive importance of space and to cover the space efficiently, we accomplished an agent-based simulation based on classification of space and pattern analysis of moving people. We developed an agent-based camera placement method considering camera performance as well as space priority extracted from path finding algorithms. We demonstrate that the method not only determinates the optimal number of cameras, but also coordinates the position and orientation of the cameras with considering the installation costs. To validate the method, we compare simulation results with videos of real materials and show experimental results simulated in a specific space.