• Journal of the military operations research society of Korea
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• v.22 no.1
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• pp.30-42
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• 1996

This study deals with an optimal firecar location and allocation models under uncertain enemy attack at the airforce base. It allocates just one firecar on the runaway and the other firecars on the headquarter of firecar company in usual situation. It is possible for several facilities at the airforce base to be attacked simultaneously by missiles enemy air attacker, other things under uncertain enemy attack. We formulate two stochastic LP location-allocation models to deal with uncertainty. One model is to locate all firecars on one site like present situation. We generate a new firecar location with a weighted average method. We call this model "centralized allocation model". The other model is to distribute firecars on several possible sites. We call this model "distributed allcoation model". Finally, we compare two models with computer experimentations on 8 airforce bases.on 8 airforce bases.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1131-1136
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• 2020

Cooperative networks enhance the performance of communication systems by combining received signals from the several relay nodes where the source node transmits signals to relay nodes. In this paper, we analyze the effect of resource allocation in cooperative networks. We assume that the cooperative networks use the conventional modulation scheme between the source and relay nodes, and adopt space-time code between the relays and destination node. Both the synchronous and differential modulations are applied for the conventional scheme and differential modulation is used for the space-time code. We consider relay location and energy allocation for resource allocation, and the performance of cooperative networks depending on the number of relay is also investigated.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.191-194
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• 2003

Location-allocation problem is known as one of the important problem faced in Industrial Engineering and Operations Research fielde. There are many variations on this problem for different applications, however, most of them consider no obstacle existing. Since the location-allocation problem with obstacles is very complex and with many infeasible solutions, no direct method is effective to solve it. In this paper we propose a hybrid Genetic Algorithm (hGA) method for solving this problem. The proposed hGA is based on Lagrangian relaxation method and Dijkstra's shortest path algorithm. To enhance the proposed hGA, a Fuzzy Logic Controller (FLC) approach is also adopted to auto-tune the GA parameters.

• Industrial Engineering and Management Systems
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• v.14 no.1
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• pp.11-21
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• 2015

The purpose of this research is to develop algorithms using the Differential Evolution Algorithm (DE) to solve a multi-objective, sources and stages location-allocation problem. The development process starts from the design of a standard DE, then modifies the recombination process of the DE in order improve the efficiency of the standard DE. The modified algorithm is called modified DE. The proposed algorithms have been tested with one real case study (large size problem) and 2 randomly selected data sets (small and medium size problems). The computational results show that the modified DE gives better solutions and uses less computational time than the standard DE. The proposed heuristics can find solutions 0 to 3.56% different from the optimal solution in small test instances, while differences are 1.4-3.5% higher than that of the lower bound generated by optimization software in medium and large test instances, while using more than 99% less computational time than the optimization software.

• 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.

• Journal of the Korea Safety Management & Science
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• v.12 no.1
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• pp.97-104
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• 2010

Expanded muti-source Weber problem (EWP), which introduced in this paper, is a reverse logistics network design problem to minimize the total transportation cost from customers thorough regional center to central center. Decision factor of EWP are the locations of regional centers and a central center. We introduce a GRASP heuristics for the EWP. In the suggested GRASP, an expanded iterative location allocation method (EILA) is introduced based on the Cooper's iterative location allocation method[3]. For the initial solution of GRASP, allocation first seed (AFSeed) and location first seed (LFSeed) are developed. The computational experiment for the objective value shows that the LFSeed is better than the AFSeed. Also the calculating time of the LFSeed is better than that of the AFSeed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.10A
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• pp.746-751
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• 2009

We propose a dynamic time allocation method in cooperative multiplexing with partial relaying system. This method uses a linear programming and considers protocol that is based on relaying of partial information bits followed by cooperative multiplexing. In this protocol, regardless of the location of relay, the allocation time for each transmission time slots are constant. Using a dynamic time allocation method with considering the location of relay, we can find optimal transmission time slots, and show that the system capacity is optimized.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.4
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• pp.750-757
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• 2017

Recently, mobile internet traffic has rapidly increased as the huge increase of the smart phone and mobile devices. D2D get attention, because D2D is known that it reduce the traffic load of the base station and also improves the reliability of the network performance. However, D2D has a problem that the efficiency decreases as interference is increased. In this paper, we propose a resource allocation scheme to use the resources efficiently when the D2D link share the cellular resources in the cellular network based the uplink. D2D communication utilizes the location information for allocating resources when the eNB know the location of all devices. The proposed scheme select some cellular user using location informations in order to ensure performance of the D2D communication. and D2D link choose cellular user that performs resource allocation using only selected cellular user. Simulation results show optimal value of resource selection in order to ensure most performance of the D2D communication.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.204-226
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• 2018

Big data processing applications have been migrated into cloud gradually, due to the advantages of cloud computing. Hadoop Distributed File System (HDFS) is one of the fundamental support systems for big data processing on MapReduce-like frameworks, such as Hadoop and Spark. Since HDFS is not aware of the co-location of virtual machines in the cloud, the default scheme of block allocation in HDFS does not fit well in the cloud environments behaving in two aspects: data reliability loss and performance degradation. In this paper, we present a novel location-aware data block allocation strategy (LDBAS). LDBAS jointly optimizes data reliability and performance for upper-layer applications by allocating data blocks according to the locations and different processing capacities of virtual nodes in the cloud. We apply LDBAS to two stages of data allocation of HDFS in the cloud (the initial data allocation and data recovery), and design the corresponding algorithms. Finally, we implement LDBAS into an actual Hadoop cluster and evaluate the performance with the benchmark suite BigDataBench. The experimental results show that LDBAS can guarantee the designed data reliability while reducing the job execution time of the I/O-intensive applications in Hadoop by 8.9% on average and up to 11.2% compared with the original Hadoop in the cloud.

• Journal of the Korean Society of Marine Environment & Safety
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• v.19 no.3
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• pp.277-284
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• 2013

To ensure that the production system of a factory is efficient, the factory layout design should consider the location and material flow plans of facilities, workshops, and storage areas. Highly productive factories need to have an optimized layout planning process, and a customized design methodology of the production system is a necessity for feasible layout planning. This paper presents a method for designing a layout module's size and shape and provides a heuristic location-allocation algorithm for the modules. The method is implemented and validated using a rich internet application-based platform. The layout design method is based on the leisure ship production process; this method can be used for designing the layout of a new factory or remodeling an existing factory and its production system. In contrast to existing layout methods, the inputs required for the proposed method, such as target products, production processes, and human-resource plans, are simple. This layout design method provides a useful solution for the initial stage of factory design.