• Journal of Korean Institute of Industrial Engineers
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• v.34 no.2
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• pp.151-159
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• 2008

An efficient location registration scheme is essential to accommodate continuously increasing mobile subscribers and to offer a variety of multimedia services with good quality. In this study, we consider a distance-based registration scheme where the number of location areas varies on the basis of cell-by-cell, not of ring-by-ring, to analyze the optimal size of the location area. Using our proposed cell-by-cell distance-based registration scheme with random walk mobility model, we analyze a variety of circumstances to obtain the optimal number of cells for location area that minimizes total signaling traffic on radio channels. From our analysis results, we show that the optimal number of cells for location area is between 4 and 6 in most cases, and our cell-by-cell distance-based location registration scheme has less signaling traffic than optimal ring-by-ring distance-based location registration scheme where optimal distance threshold is 2 (thus the optimal number of cells for location area is 7).

• Korean Management Science Review
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• v.29 no.1
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• pp.143-152
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• 2012

Location area planning (LAP) problem is to partition the cellular/mobile network into location areas with the objective of minimizing the total cost in location management. The minimum cost has two components namely location update cost and searching cost. Location update cost is incurred when the user changes itself from one location area to another in the network. The searching cost incurred when a call arrives, the search is done only in the location area to find the user. Hence, it is important to find a compromise between the location update and paging operations such that the cost of mobile terminal location tracking cost is a minimum. The complete mobile network is divided into location areas. Each location area consists of a group of cells. This partitioning problem is a difficult combinatorial optimization problem. In this paper, we use particle swarm optimization (PSO) to obtain the best/optimal group of cells for 16, 36, 49, and 64 cells network. Experimental studies illustrate that PSO is more efficient and surpasses those of precious studies for these benchmarking problems.

• Korean Management Science Review
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• v.25 no.2
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• pp.73-80
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• 2008

The location area planning is to assign cells to the location areas of a wireless communication network in an optimum manner. The two important cost components are cost of location update and cost of paging that are of conflicting in nature; i.e., minimizing the registration cost might increase the search cost. Hence, it is important to find a compromise between the location update and paging operations such that the cost of mobile terminal location tracking cost is a minimum. The complete mobile network is divided into location areas. Each location area consists of a group of cells. In fact this is shown to be an NP-complete problem in an earlier study. In this paper, we use an ant colony optimization method to obtain the best/optimal group of cells for a given a network.

• Journal of The Geomorphological Association of Korea
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• v.27 no.4
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• pp.89-112
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• 2020

The purpose of this study is as follows: First, we restore the optimal topographical environment of the Bronze Age settlements in the Yongdu Stream and its surrounding area in Asan City. Second, we reveal the relative importance of the topographical factors that the Bronze Age people considered when selecting their dwelling locations. We compared and analyzed topographical factors (ridge scale, ridge direction, slope direction of the ridge, micro-landform of the ridge, position of the ridge) from the ridge's environmental perspective of 123 Bronze Age dwellings (hereinafter referred to as dwellings) found in the survey area for that purpose. The results are as follows: First, from a macro perspective, the optimal topographical environment for the location of the Bronze Age settlement is the second ridge that have the E-W direction. And from a micro perspective, it is the southeast direction slope of the Crest slope at the summit. Second, it appears that the Bronze Age people have taken important consideration in determining the location of their dwelling in the following order: ① position (eg. summit), ② micro-landform (eg. Crest slope, Upper slope), ③ slope direction (eg. southward, South, Southeast), ④ scale (eg. sub-ridge, secondary, tertiary), ⑤ direction (eg. E-W, NNE-SSE).

• Journal of Korean Society on Water Environment
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• v.24 no.2
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• pp.180-184
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• 2008

A distributed hydrologic model of an urban drainage area on Bugok drainage area in Oncheon stream was developed and combined with a optimization method to determine the optimal location and number of best management practices (BMPs) for storm water runoff reduction. This model is based on the SCS-CN method and integrated with a distributed hydrologic network model of the drainage area using system of 4,211 hydrologic response units (HRUs). Optimal location is found by locating HRU combination that leads to a maximum reduction in peak flow at the drainage outlet in this model. The results of this study indicate the optimal locations and numbers of BMPs, however, for more exact application of this model, project cost and SCS-CN reduction rate of structural facilities such infiltration trench and pervious pavement will have to be considered.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.2
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• pp.46-53
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• 2016

In mobile communication systems, location management deals with the location determination of users in a network. One of the strategies used in location management is to partition the network into location areas. Each location area consists of a group of cells. The goal of location management is to partition the network into a number of location areas such that the total paging cost and handoff (or update) cost is a minimum. Finding the optimal number of location areas and the corresponding configuration of the partitioned network is a difficult combinatorial optimization problem. This cell grouping problem is to find a compromise between the location update and paging operations such that the cost of mobile terminal location tracking is a minimum in location area wireless network. In fact, this is shown to be an NP-complete problem in an earlier study. In this paper, artificial bee colony (ABC) is developed and proposed to obtain the best/optimal group of cells for location area planning for location management system. The performance of the artificial bee colony (ABC) is better than or similar to those of other population-based algorithms with the advantage of employing fewer control parameters. The important control parameter of ABC is only 'Limit' which is the number of trials after which a food source is assumed to be abandoned. Simulation results for 16, 36, and 64 cell grouping problems in wireless network show that the performance of our ABC is better than those alternatives such as ant colony optimization (ACO) and particle swarm optimization (PSO).

• Journal of Korean Society of Industrial and Systems Engineering
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• v.5 no.7
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• pp.9-15
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• 1982

The rectilinear-distance location problem combines the property of being a very appropriate distance measure for a large number of location problems and the property of being very simple to treat analytically. An obvious question to be asked at the optimal point which is obtained by the rectilinear distance method is, "what if the point is not available as a location site\ulcorner." The point may, for example, be inaccessible or may coincide with the location of another structure, a river, or a municipal park. In this case, one approach that may be employed is to construct contour lines (also called iso-cost or level curves) of the cost function. Contour lines provide considerable insight into the shape of the surface of the total cost function as well as a useful means of evaluating alternative locations for the new facility. But, when there is an obstacle which divides the application area into two. The optimal location(which is acquired by the rectilinear distance method) is not coincide with the minimal cost point and the contour line is occasionally of no use, this paper shows the method of finding a way to decide an optimal point of single facility location in this case.this case.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.790-793
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• 2008

Recently, Intelligent Excavating System(IES) for earthwork automation is on progress since the end of 2006 as a part of construction technology innovation projects in Ministry of Land, Transport and Maritime Affairs. Task Planning System(TPS), one of the detail core technologies of IES, is an optimal work planning system in conditions of effectiveness, safety and economic efficiency by analyzing the work environment data based on earthwork design and work environment recognition technology. For effective earthwork planning, the location of platform must be the most optimal spot for minimization of time, maximization of productivity and reduction of overlapped work spaces and unnecessariness. Besides, the decision of optimal platform location is to be based on the specifications and then is able to be converted with the local area calculation algorithm. This study explains the decision of optimal platform location on the basis of local area from the work space separate process and judges the effectiveness.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.119-126
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• 2004

Location management is very important issue in wireless communication system to trace mobile users' exact location. In this study, we propose a dynamic location area management scheme which determines the size of dynamic location area considering each user's characteristic. In determining the optimal location area size, we consider the measurement data as well as the historical data, which contains call arrival rate and average speed of each mobile user. In this mixture of data, the weight of historical data is derived by linear searching method which guarantees the minimal cost of location management. We also introduce the regularity index which can be calculated by using the autocorrelation of historical data itself. Statistical validation shows that the regularity index is the same as the weight of measurement data. As a result, the regularity index is utilized to incorporate the historical data into the measurement data. By applying the proposed scheme, the location management cost is shown to decrease. Numerical examples illustrate such an aspect of the proposed scheme.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.135-143
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• 2012

This paper suggests the optimal blood distribution center algorithm that satisfies the minimum total transportation cost and within the allowable distribution time $T^*$. Zhang and Yang proposes shifting the location of each point that has less than the average distance of two maximum distance points from each point. But they cannot decide the correct facility location because they miscompute the shortest distance. This algorithm computes the shortest distance $l_{ij}$ from one area to another areas. Then we select the $v_i$ area to thecandidate distribution center location such that $_{max}l_{ij}{\leq}L^*$ and the $v_i$ such that $l_{ij}-L^*$ area that locates in ($v_i,v_k$) and ($v_j,v_l$) from $P_{ij}=v_i,v_k,{\cdots},v_l,v_j$ path and satisfies the $_{max}l_{ij}{\leq}L^*$ condition. Finally, we decide the candidate distribution area that has minimum transportation cost to optimal distribution area.