• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.4
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• pp.61-72
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• 2004

In this paper, we design sampling inspections and service capacities simultaneously for multi-products. Particularly, we extend Kim(2003) by introducing the fixed cost of providing services. We show that, due to the fixed cost considered, the cost function of a product is no longer linear or convex in terms of the level of service provision, and the total inspection is prefered to the small level of service capacity which results in high burden of the fixed cost. And we develop a simple framework to deal with this joint design problem for a product. Also we consider the problem of allocating the given number of the total service capacities among products. A dynamic programming algorithm is developed to determine the optimal allocation which minimizes the overall total cost of the system and the optimal allocation can be obtained with the considerably smaller computations than the total number of possible allocations. The results can be used to support planning decisions and to aid the joint design of inspections and service capacities for products.

• International Journal of Contents
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• v.8 no.4
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• pp.7-11
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• 2012

Cloud Computing can be viewed as a dynamically-scalable pool of resources. Virtualization is one of the key technologies enabling Cloud Computing functionalities. Virtual machines (VMs) scheduling and allocation is essential in Cloud Computing environment. In this paper, two dynamic VMs scheduling and allocating schemes are presented and compared. One dynamically on-demand allocates VMs while the other deploys optimal threshold to control the scheduling and allocating of VMs. The aim is to dynamically allocate the virtual resources among the Cloud Computing applications based on their load changes to improve resource utilization and reduce the user usage cost. The schemes are implemented by using SimPy, and the simulation results show that the proposed adaptive scheme with one threshold can be effectively applied in a Cloud Computing environment both performance-wise and cost-wise.

• ETRI Journal
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• v.25 no.4
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• pp.211-218
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• 2003

This paper presents a dynamic resource allocation algorithm with multi-frequency time-division multiple access for the return link of interactive satellite multimedia networks such as digital video broadcasting return channel via satellite systems. The proposed timeslot assignment algorithm, called the very efficient dynamic timeslot assignment (VEDTA) algorithm, gives an optimal assignment plan within a very short period. The optimality and computational efficiency of this algorithm demonstrate that it will be useful in field applications.

• Journal of the military operations research society of Korea
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• v.24 no.2
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• pp.130-145
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• 1998

This paper is concerned with the optimization of a system reliability. Two kinds of the reliability model for optimal allocation of parallel redundancy are considered. The algorithm for solving the optimal redundancy problem is proposed by the use of dynamic programming(DP) method. The problem is approached with a standard DP formulation and the DP algorithm is applied to the model and then the optimal solution is found by the backtracking method. The method is applicable to the models having no constraints or having a cost constraint subject to a specified minimum requirement of the system reliability. A consequence of this study is that the developed computer program package are implemental for the optimization of the system reliability.

• Journal of IKEEE
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• v.28 no.3
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• pp.440-444
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• 2024

This paper presents a solution to the frequency coexistence problem between low earth orbit (LEO) satellite networks and other services by utilizing genetic algorithms. Non-terrestrial network (NTN) utilizing LEO satellites have mobility and need to address interference issues that may occur when sharing frequencies with terrestrial services according to propagation rules. In this study, we model the interference scenario based on the NTN operation scenario proposed by 3GPP, and derive the optimal channel allocation scheme for NTNs to protect terrestrial services while satisfying the minimum quality of service (QoS) through genetic algorithm. The simulation results show that the proposed method outperforms the existing fixed assignment method and graph coloring method, and enables efficient frequency sharing.

• Journal of Communications and Networks
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• v.18 no.1
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• pp.50-64
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• 2016

Nowadays, smart meter (SM) technology is widely effectively used. In addition, power allocation (PA) and channel selection (CS) are considered problems with many proposed approaches. In this paper, we will suggest a specific scenario for an SM configuration system and show how to solve the optimization problem for transmission between SMs and the data concentrator unit (DCU), the center that collects the data from several SMs, via simulation. An efficient CS with PA scheme is proposed in the TV white space system, which uses the TV band spectrum. On the basic of the optimal configuration requirements, SMs can have a transmission schedule and channel selection to obtain the optimal efficiency of using spectrum resources when transmitting data to the DCU. The optimal goals discussed in this paper are the maximum capacity or maximum channel efficiency and the maximum allowable power of the SMs used to satisfy the quality of service without harm to another wireless system. In addition, minimization of the interference to the digital television system and other SMs is also important and needs to be considered when the solving coexistence scenario. Further, we propose a process that performs an interference analysis scheme by using the spectrum engineering advanced Monte Carlo analysis tool (SEAMCAT), which is an integrated software tool based on a Monte-Carlo simulation method. Briefly, the process is as follows: The optimization process implemented by genetic evolution optimization engines, i.e., a genetic algorithm, will calculate the best configuration for the SM system on the basis of the interference limitation for each SM by SEAMCAT in a specific configuration, which reaches the solution with the best defined optimal goal satisfaction.

• Journal of Intelligence and Information Systems
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• v.12 no.2
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• pp.99-123
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• 2006

In an effect to composite an optimal supply chain, this study has introduced an agent-based negotiation as a method to assign a lot of orders to a large number of participants. As a resources allocation mechanism to form a strategic cooperation based on information sharing between supply chain members(buyers, manufacturers, suppliers), this agent negotiation provides coordination functions allowing all participants to make a profit and accomplishing Pareto optimum solution from the viewpoint of a whole supply chain. A SET model-based scheduling takes into consideration both earliness production cost and tardiness production cost, along with a competitive relationship between multiple participants. This study has tried to prove that the result of an agent-based negotiation is a Pareto optimal solution under the dynamic supply chain environment, establishing the mathematical formulation for a performance test, and making a comparison with the heuristic Branch & Bound method.

• Journal of the Korean Regional Science Association
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• v.13 no.2
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• pp.75-92
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• 1997

This paper is concerned with an estimation of optimal investment of road sector in 1996-2005. The main method is a Computable General Equilibrium (CGE) Model for Korea in which the optimal solution is derived in a recursively dynamic path. The model is composed of three main modules: the supply, the demand and the price. In this paper, the investment demand for the road is optimized with subject to national economic growth and price inflation. If the annual inflation level and the economic growth rate during 1996-2005 are set to 4.5%-5.0% and 6.0%-6.5% respectively, the optimal demand for the road investment is estimated as 155.1-180.1 trillion Won or 3.33%-3.89% of the GDP for ten years. It implies that the additional increase of the road investment by 0.61%-1.15% of the GDP is required for sustainable economic development, since the share of the road investment in the GDP of the latest 5 years has stayed around 2.27%. However, it is necessary to reduce construction investments on housing as well as to promote private financing of the road in order to maximize an efficiency of resource allocation.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.207-210
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• 2009

An efficient algorithm to compress high dynamic range (HDR) videos is proposed in this work. We separate an HDR video sequence into a tone-mapped low dynamic range (LDR) sequence and a ratio sequence. Then, we encode those two sequences using the standard H.264/AVC codec. During the encoding, we allocate a limited amount of bit budget to the LDR sequence and the ratio sequence adaptively to maximize the qualities of both the LDR and HDR sequences. While a conventional LDR decoder uses only the LDR stream, an HDR decoder can reconstruct the HDR video using the LDR stream and the ratio stream. Simulation results demonstrate that the proposed algorithm provides higher performance than the conventional methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.1A
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• pp.58-64
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• 2009

In this paper, we propose an dynamic random channel allocation scheme increasing probability of channel acquisition and reducing delay by limiting the number of minimum RCHs(Random CHannels) as an optimal factor $\beta$. The MAC protocol of HIPERLAN/2 is based on TDMA/TDD and MT(Mobile Terminal) can obtain chance of traffic transmission through channel competition in RCH period. And AP(Access Point) can dynamically schedule the number of RCHs based on the number of the collision in each RCH of the previous frame. Therefore, the proposed scheme increases a probability of channel acquisition and reduces delay by means of guaranteeing the number of minimum RCHs. With a practical Internet traffic, it is concluded that by the proposed scheme the delay reduction of the order of 19% and slightly better throughput are obtained compared to the conventional algorithm.