• The KIPS Transactions:PartC
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• v.14C no.1 s.111
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• pp.73-80
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• 2007

In conventional on-demand mobile ad hoc routing algorithms, an alternate path is sought only after an active path is broken. It incurs a significant cost in terms of money and time in detecting the disconnection and establishing a new route. In this thesis, we propose proactive route selection and maintenance to conventional mobile ad hoc on-demand routing algorithms. The key idea for this research is to only consider a path break to be likely when the signal power of a received packet drops below an optimal threshold value and to generate a forewarning packet. In other words, if a path is lost with high probability, the neighboring node that may easily be cut off notifies the source node by sending a forewarning packet. Then the source node can initiate route discovery early and switched to a reliable path potentially avoiding the disconnection altogether. For the simulational study, network simulator(NS2) is used. The result of simulation shows that the algorithm significantly improves the performance of networks comparing to conventional on-demand routing protocols based on DSR and AODV in terms of packet delivery ratio, packet latency and routing overhead.

• Journal of the Society of Disaster Information
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• v.16 no.1
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• pp.96-110
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• 2020

Recently, due to global warming, it is easily exposed to various disasters such as fire, flood, and earthquake. In particular, large-scale disasters have continuously been occurring in crowded areas such as traditional markets, facilities for the elderly and children, and public facilities where various people stay. Purpose: This study aims to detect a fire occurred in crowded facilities early in the event to analyze and provide an optimal evacuation route using big data and advanced technology. Method: The researchers propose a new algorithm through context-aware 3D object model technology and A* algorithm optimization and propose a scenario-based optimal evacuation route selection technique. Result: Using the HPA* E algorithm, the evacuation simulation in the event of a fire was reproduced as a 3D model and the optimal evacuation route and evacuation time were calculated for each scenario. Conclusion: It is expected to reduce fatalities and injuries through the evacuation induction technique that enables evacuation of the building in the shortest path by analyzing in real-time via fire detection sensors that detects the temperature, flame, and smoke.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.4
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• pp.175-187
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• 2004

We consider the simultaneous selection of part routes for multiple part types in Flexible Manufacturing Systems (FMSs). Using an optimization framework we investigate two alternative route assignment policies. The one, called routing mix policy in the literature, specifies the optimal proportion of each part type to be produced along its alternative routes, assuming that the proportions can be kept during execution. The other one, which we propose and call pallet allocation policy, partitions the pallets assigned to each part type among the routes. The optimization framework used is a nonlinear programming superimposed on a closed queueing network model of an FMS which produces multiple part types with distinct repeated visits to certain workstations. The objective is to maximize the weighted throughput. Our study shows that the simultaneous use of multiple routes leads to reduced bottleneck utilization, improved workload balance, and a significant increase in the FMS's weighted throughput, without any additional capital investments. Based on numerical work, we also conjecture that pallet allocation policy is more robust than routing mix policy, operationally easier to implement, and may yield higher revenues.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.402-410
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• 2004

In this paper, an optimal design method of clonal selection based Fuzzy-Neural Networks (FNN) model for complex and nonlinear systems is presented. The FNNs use the simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rule. Also Advanced Clonal Selection (ACS) is proposed to find the parameters such as parameters of membership functions, learning rates and momentum coefficients. The proposed method is based on an Immune Algorithm (IA) using biological Immune System and The performance is improved by control of differentiation rate. Through that procedure, the antibodies are producted variously and the parameter of FNN are optimized by selecting method of antibody with the best affinity against antigens such as object function and limitation condition. To evaluate the performance of the proposed method, we use the time series data for gas furnace and traffic route choice process.

• Information Systems Review
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• v.10 no.1
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• pp.115-133
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• 2008

The third-party logistics industry mainly delivers goods from a place to an arrival place on behalf of the freight owner. To handle the work, they need a transportation route including transportation equipment between the starting place and the arrival place, schedule information for departure/arrival and transportation cost. Actually, automatic searching for an optimal transportation route, which considers arrival and departure points for intermodal transportation, is not a simple problem. To search efficiently transportation route, the collection of schedule information for intermodal transportation and transportation route generation have become critical and vital issues for logistics companies. Usually, they manually make a plan for a transportation route by their experience. Because of this, they are limited in their ability if there is too much cargo volume and a great many transactions. Furthermore, their dependence on the conventional way in doing business causes an inefficient selection of transporters or transportation routes. Also, it fails to provide diverse alternatives for transportation routes to the customers, and as a result, increases logistics costs. In an effort to solve these problems, this study aims to develop a route planning system based on agent, which can collect scattered schedule information on the Web. The route planning system also has an algorithm for transportation route generation in intermodal transportation.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.542-544
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• 2005

Recently, the principal processes of T/L design tend to computerize and therefore integrated T/L design system has been developed. Since, it makes the automatic selection of T/L route, tower position and optimum design possible, computerized design method is applied all over the world. KEPCO introduced Optimal PowerLINE for T/L design in Myanmar 500kV project that is as a part of overseas project. And as a result of that work, effective and economical design was carried out. This paper presents the comparative analysis between Previous method and Optimal PowerLINE method for investigating practical application to Myanmar 500kV T/L design.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.3
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• pp.273-283
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• 2000

In this paper we suggest an optimal design method of Fuzzy-Neural Networks(FNN) model for complex and nonlinear systems. The FNNs use the simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rule. And we use a HCM(Hard C-Means) Clustering Algorithm to find initial parameters of the membership function. The parameters such as parameters of membership functions learning rates and momentum weighted value is proposed to achieve a sound balance between approximation and generalization abilities of the model. According to selection and adjustment of a weighting factor of an aggregate objective function which depends on the number of data and a certain degree of nonlinearity (distribution of I/O data we show that it is available and effective to design and optimal FNN model structure with a mutual balance and dependency between approximation and generalization abilities. This methodology sheds light on the role and impact of different parameters of the model on its performance (especially the mapping and predicting capabilities of the rule based computing). To evaluate the performance of the proposed model we use the time series data for gas furnace the data of sewage treatment process and traffic route choice process.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1D
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• pp.195-202
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• 2006

The infiltration route analysis is a military application using geospatial information technology. The result of the analysis would present vulnerable routes for potential enemy infiltration. In order to find the susceptible routes, optimal path search algorithms (Dijkstra's and $A^*$) were used to minimize the cost function, summation of detection probability. The cost function was produced by capability of TOD (Thermal Observation Device), results of viewshed analysis using DEM (Digital Elevation Model) and two related geospatial information coverages (obstacle and vegetation) extracted from VITD (Vector product Interim Terrain Data). With respect to 50m by 50m cells, the individual cost was computed and recorded, and then the optimal infiltration routes was found while minimizing summation of the costs on the routes. The proposed algorithm was experimented in Daejeon region in South Korea. The test results show that Dijkstra's and $A^*$ algorithms do not present significant differences, but A* algorithm shows a better efficiency. This application can be used for both infiltration and surveillance. Using simulation of moving TOD, the most vulnerable routes can be detected for infiltration purpose. On the other hands, it can be inversely used for selection of the best locations of TOD. This is an example of powerful geospatial solution for military application.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.3
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• pp.3-9
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• 2013

As interest in green growth picks up, the importance of bicycles which are an environment friendly means of communication has been magnified. However, bicycle routes which are the base of bicycles are designed without considering topographic elements and thus many users are experiencing inconvenience in using bicycles. The present study presents a routing technique to select optimal routes when selecting routes in commuting to school utilizing bicycles. To this end, a formula for optimum route calculation considering slope and intersections was drawn and a method to select optimum routes by applying modified Dijkstra Algorithms was studied. According to the results, the bicycle routes for commuting to school should be selected by the shortest time rather than the shortest distances to the destination, because it required reach the destination faster. Therefore when selecting the routes, it must be based on the shortest time considering waiting time due to crosswalks or crossroads and speed variations due to slopes.

• Journal of the Korean Society for Railway
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• v.10 no.2 s.39
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• pp.112-116
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• 2007

In this paper, we proposed a selection and application recommendations of ZnO arresters for DC electric traction vehicles. To decide the Continuous Operating Voltage($U_C$), the Rated Voltage($U_r$), and the Nominal Discharge Current(In), we measured and analyzed system voltages and surge currents flowing the arrester installed on a DC electric traction vehicle under running state. System voltages measured up to 1,800 V in 1,500 V-system, and surge currents were recorded up to 3 times per a running-service-route and their magnitudes were ranges of $150A{\sim}2kA$. From these results and a standard EN50163, we could proposed $U_C$, $U_r$, and In available for the 1,500 VDC electric traction vehicles.