• Korean Management Science Review
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• v.26 no.1
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• pp.197-208
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• 2009

In this paper, we study stochastic maximal covering location problem considering floating population. Traditional maximal covering location problem assumed that number of populations at demand point is already known and fixed. In this manner, someone who try to solve real world maximal covering location problem must consider administrative population as a population at demand point. But, after observing floating population, appliance of population in steady-state is more reasonable. In this paper, we suggest revised numerical model of maximal covering location problem. We suggest heuristic methodology to solve large scale problem by using genetic algorithm.

• Journal of the Korean Operations Research and Management Science Society
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• v.31 no.4
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• pp.139-155
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• 2006

The facility location problem of this paper is distinguished from the maximal covering location problem and the flxed-charge facility location problem. We propose the maximal profiting location problem (MPLP) that is the facility location problem maximizing profit with multi-product. We apply to the simulated annealing algorithm, the stochastic evolution algorithm and the accelerated simulated annealing algorithm to solve this problem. Through a scale-down and extension experiment, the MPLP was validated and all the three algorithm enable the near optimal solution to produce. As the computational complexity is increased, it is shown that the simulated annealing algorithm' is able to find the best solution than the other two algorithms in a relatively short computational time.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2007.11a
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• pp.316-321
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• 2007

The hierarchical covering location problem emphasizes the issue of locating of hierarchical facilities in order to maximize the number of customers that can be covered. In the classical HCLP(Hierarchical Covering Location Problem), it is assumed that the customers are covered completely if they are located within a specific distance from the facility, and not covered otherwise. The generalized HCLP is introduced that the coverage of customers is measured to be any real value rather than 0 or 1, where the service level may decrease according to the distance. Mixed integer programming formulation for the generalized HCLP is suggested with a partial coverage of service. Solutions are found using OPL Studio, and are evaluated for various cases.

• Journal of Korean Society of Transportation
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• v.27 no.4
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• pp.103-113
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• 2009

Quick accident spot reaching of 119ERU is the most important role in decrease of accident depth. If 4 minutes of wounded person pass after cardiac arrest, brain damage is begun. and If 10 minutes of wounded person pass after cardiac arrest, possibility to die rises. Accordingly, when establish 119ERU, need to consider travel time to traffic accidents spot. This treatise groped a facility location problem using SCLM and minisum location problem mutually. And existent minisum location problem has a problem that maximum travel time exceed $\lambda$. ERU to need in present situation and also can reduce average travel time. so this treatise propose modified minisum location problem. In case applying modified minisum location theory, 119ERU can arrive all demand and that is optimized about demand and travel time. Can minimise figure of 119 first aids to need in present situation applying this way, and also can reduce average passing time. Finally, this way can minimise figure of 119ERU to need in present situation and also can reduce average travel time.

• Journal of the Korean Operations Research and Management Science Society
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• v.15 no.2
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• pp.97-104
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• 1990

The problem is a variation of the weighted set-covering problem (SCP) which requires the minimum-cost cover to be self-covering. It is shown that direct extension of the well-known greedy heuristic for SCP can have an arbitrarily large error in the worst case. It remains an open question whther these exists a greedy heuristic with a finite error bound.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.4
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• pp.43-56
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• 2009

In korean peninsular, aircraft defense with SAM (Surface-to-Air Missile) is very important because of short range of combat space in depth. Effective and successful defense operation largely depends on two factors, SAM's location and the number of SAM for each target based on missile's availability in each SAM's location. However, most previous papers have handled only the former. In this paper, we developed Set covering model which can handle both factors simultaneously and Multi-heuristic algorithm for solving allocation problem of the batteries and missile assignment problem in each battery. Genetic algorithm is used to decide optimal location of the batteries. To determine the number of SAM, a heuristic algorithm is applied for solving missile assignment problem. If the proposed model is applied to allocation of SAM, it will improve the effectiveness of air defense operations.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.1
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• pp.43-50
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• 2013

This paper aims to determine the optimal location of expressway patrol vehicle stations that minimizes additional troubles caused by the delay of crash treatments. To do this, we formulate a maximum covering problem and a p-center problem weighted by crash frequency, using the shortest distance as the criteria for allocating service district, and we employ the Lagrangian relaxation algorithm to solve the former and Daskin's heuristic algorithm to solve the latter, respectively. Based on crash data of Korean expressways, the results from the proposed models are compared with the current location of patrol vehicle stations by using several indices as the level of service for crash treatment, such as maximum crash-weighted distance, average crash-weighted distance, and average access distance. The results show that the proposed models improve average access distance and time by about 10km and 10min, respectively. When allocation for service district is changed only with the fixed current location, the level of service can be also improved. The models and results proposed in this paper can contribute to improving the level of service for crash treatment on expressways. They can also provide the theoretical basis on the location decision for other various emergency facilities, and the allocation decision for floating service districts according to time-period crash data.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.1
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• pp.121-135
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• 2013

This paper propose an efficient algorithm for selecting electric bus charging facility location. In nature, the optimal charging facility location problem is similar to Set Covering Problem. Set Covering Problem is the problem of covering all the rows of an $m{\times}n$ matrix of ones and zeros by a subset of columns with a minimal cost. It has many practical applications of modeling of real world problems. The Set Covering Problem has been proven to be NP-Complete. In order to overcome the computational complexity involved in seeking optimal solutions, this paper present an enhanced greedy algorithm and simulated annealing algorithm. In this paper, we apply the developed algorithm to Seoul's public bus system.

• 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 Institute of Industrial Engineers
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• v.30 no.2
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• pp.93-106
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• 2004

This paper studied a maximal covering location problem with cost restrictions, to maximize level of service within predetermined cost. It is assumed that all demand have to be met. If the demand node is located within a given range, then its demand is assumed to be covered, but if it is not, then its demand is assumed to be uncovered. An uncovered demand is received a service but at an unsatisfactory level. The objective function is to maximize the sum of covered demand, Two heuristics based on the Lagrangean relaxation of allocation and decoupling are presented and tested. Upper bounds are found through a subgradient optimization and lower bounds are by a cutting algorithm suggested in this paper. The cutting algorithm enables the Lagrangean relaxation to be proceeded continually by allowing infeasible solution temporarily when the feasible solution is not easy to find through iterations. The performances are evaluated through computational experiments. It is shown that both heuristics are able to find the optimal solution in a relatively short computational time for the most instances, and that decoupling relaxation outperformed allocation relaxation.