• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.44
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• pp.33-46
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• 1997

The location decision problem for distribution center is one of the most important problem in business logistics system. Because the proportion of holding and transportation cost to physical distribution cost in our country exceed the 60%, a corporation must feel strong pressure to investigate the location problem for distribution center. This paper presents an algorithm for determining the best location of distribution center in consideration with physical distribution cost, demand, and customer location. The methods of determining the distribution center location is that firstly many of proposed sites are built up where demand position is distributed, and then optimal location of distribution center is selected.

• Journal of the Korean Operations Research and Management Science Society
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• v.8 no.1
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• pp.27-30
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• 1983

The purpose of this paper is to find a new method for the warehouse location problem. Akinc and Khumatvala developed a branch and bound algorithm for a one-stage problem, that is, plants and warehouses are at the same location. This paper extends this method to a two-stage problem, that is, plants, warehouses and users are located at different sites, and further this paper allows direct flows from plants to users. The new method is tested at Perkins-Elmer. The test shows that the algorithm is efficient.

• Journal of the Korean Regional Science Association
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• v.14 no.1
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• pp.91-107
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• 1998

Waste disposal problem is one of the most important social welfare indicators in urban area, because the volume of waste generated from urban area is remarkable. So far most waste of Seoul has been disposed at landfills. However, this landifill disposal method is confronted with several difficulties in recent. As public concern on environmental problem increases and autonomy system is settled down, local community people of the landfills refuse to receive the waste produced other places any more. It brought reginal confliction problem between waste sending and receiving by refusing to accept waste from certain region. Furthermore, it is difficult to find another place to fill up the waste, while the existing landfiis is reached at the limit in the near future. In terms of environmental aspects landfill method is not the best way to dispose waste. It contaminates the soil and ground/underground water by leaking water containing many serious pollutants as well as offensive oder. In terms of equity, this waste disposal method is not fair. Environmental pollution causes damage to residence near to the landfills, while the waste produced other places. In order to satisfy the equity aspect, the waste generated a region should be disposed within the region. Incineration of Waste has been provided as the alternative. Government plans to construct waste incinerator in every anatomy, so the waste produced by local community is disposed within their local autonomous area. However, the location decision is not easy, since waste incinerator is one of the facilities to the community people. We can not apply the existing location models for this problem, because they show strong NIMBY phenomenon for the location. The location of waste incinerator should be determined very carefully with consideration of various location factors and criteria. This study proposes a methodology for determining the location of the waste incinerators by utilizing GIS, which is a power research tool for location decision where various geographical factors related. We drive the location factors which should be considered in the determination of waste incinerators. They involve environmental, socio-economic, and institutional factors. In first, we eliminate the area which is located within the environmental location criteria such as slope, fault line, distance to river, and then eliminate ares which is conflict with the social and institutional criteria.

• Journal of Korean Institute of Industrial Engineers
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• v.26 no.4
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• pp.384-391
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• 2000

Most of the previous works on classical location models are based on the assumption that the value(or utilities) of inventory remains constants over time. In this study a special case of location problem is studied for both ameliorating and deteriorating items in two-echelon supply-chain management such as agricultural and fishery products. The objective of this study is to determine the minimum number of storage facilities among a discrete set of location sites so that the probability for each customer to be covered is not less than a critical value. We have formulated this problem using stochastic set-covering problem which can be solved by 0-1 programming method. Also we developed a computer program and applied to a set of problems for fish culture storage and distribution centers and the sample results well show the impact of ameliorating and deteriorating rate on the location problem. For the further study, a graphical user-interface with visualization for input and output is needed to be developed.

• 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 the Korean Operations Research and Management Science Society
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• v.31 no.2
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• pp.141-155
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• 2006

In this paper, we address an extended hub-and-spoke transportation network design problem (EHSNP). In the existing hub location problems, the location and number of spokes, and shipments on spokes are given as input data. These may, however, be viewed as the variables according to the areas which they cover. Also, the vehicle routing in each spoke needs to be considered to estimate the network cost more correctly. The EHSNP is a problem of finding the location of hubs and spokes, and pickup/delivery routes from each spoke, while minimizing the total related transportation cost in the network. The EHSNP is an integrated problem that consists of several interrelated sub-problems. To solve EHSNP, we present an approach based on a symbiotic evolutionary algorithm (symbiotic EA), which are known as an efficient tool to solve complex integrated optimization problems. First, we propose a framework of symbiotic EA for EHSNP and its genetic elements suitable for each sub-problem. To analyze the proposed algorithm, the extensive experiments are performed with various test-bed problems. The results show that the proposed algorithm is promising in solving the EHSNP.

• Journal of the Korea Institute of Military Science and Technology
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• v.7 no.4 s.19
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• pp.61-69
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• 2004

This paper presents a new analytical method for estimating the location of a target using directional data. Based on a nonlinear programming (NLP) problem formulated for the line method, which is a well known algorithm for two-dimensional location estimation, we present a method to find an optimal solution for the problem. Then we present a two-stage method for better location estimation based on the NLP problem. In addition, another two-stage method is presented for location estimation problems in which different types of observers are used to obtain directional data based on the analysis of the maximum likelihood estimate of the target location. The performance of the suggested method is evaluated through simulation experiments, and results show that the two-stage method is computationally efficient and highly accurate.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.17-24
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• 2006

We consider the sensor location problem (SLP) on a given sensor field. We present the sensor field as grid of points. There are several types of sensors which have different detection ranges and costs. If a sensor is placed in some point, the points inside of its detection range can be covered. The coverage ratio decreases with distance. The problem we consider in this thesis is called multiple-type differential coverage sensor location problem (MDSLP). MDSLP is more realistic than SLP. The coverage quantities of points are different with their distance form sensor location in MDSLP. The objective of MDSLP is to minimize total sensor costs while covering every sensor field. This problem is known as NP-hard. We propose a new integer programming formulation of the problem. In comparison with the previous models, the new model has a smaller number of constraints and variables. This problem has symmetric structure in its solutions. This group is used for pruning in the branch-and-bound tree. We solved this problem by branch-and-cut(B&C) approach. We tested our algorithm on about 60 instances with varying sizes.

• Industrial Engineering and Management Systems
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• v.3 no.2
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• pp.92-99
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• 2004

We consider the ATM switching node location problem (ANLP). In this problem, there are two kinds of facilities, hub facilities and remote facilities, with different capacities and installation costs. We are given a set of customers with each demand requirements, a set of candidate installation sites of facilities, and connection costs between facilities. We need to determine the locations to place facilities, the number of facilities for each selected location, the set of customers who are connected to each installed hub via installed remote facilities with minimum cost, while satisfying demand requirements of each customer. We formulate this problem as a general integer programming problem and solve it to optimality. In this paper, we present a preprocessing procedure to tighten the formulation and develop a branch-and-price algorithm. In the algorithm, we consider the integer knapsack problem as the column generation problem. Computational experiments show that the algorithm gives optimal solutions in a reasonable time.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.3
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• pp.209-214
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• 2018

This paper suggests simple algorithm of facility location problem in perishable commodities that satisfy with minimum total transportation cost and within the transportation time constraint $L^*$. For this problem, Lee[4] suggests very complex algorithm that decides candidate facility locations, computes total transportation cost for each candidate facility location, then moving the location to optimal location for top two facilities. On the other hand, this paper simply determines the candidate facility locations within $L^*$ using subtree concept, and decides optimal minimal total transportation cost for top two locations in centralized area of required quantity using neighborhood concept.