• Journal of the Korean Statistical Society
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• 제22권2호
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• pp.235-247
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• 1993

The predictive density function of a potential future observation and its first four moments are obtained in this paper to study the effects of a non-normal prior of the unknown mean of a normal population. The derived predictive density function is modified to study changes in utility curves, used to choose the optimum treatment from a given set of treatments, at a given level of stimulus due to slight deviations from normality of the prior distribution. Numerical illustrations are provided to exhibit some effectsl.

• Communications for Statistical Applications and Methods
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• 제6권3호
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• pp.749-754
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• 1999

The cost is known to be proportional to the size of sample. We consider a cost function of the form Cost=c1np+c2npmq where c1, c2 p, and q are all positive constants. This cost function is to be used in finding an optimal allocation in two-stage cluster sampling. The optimal allocations of n and m gives the properties of uniqueness under some conditions and of monotonicity with p>0 when q=1.

• 재무관리연구
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• 제2권1호
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• pp.55-75
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• 1986

This article is to analyse the economic efficiency of capital market, which plays a role of resource allocation in terms of financial claims such as stock and bond. It provides various contributions to the welfare theoretical aspects of modern capital market theory. The key feature that distinguishes the theory described here from traditional welfare theory is the presence of uncertainty. Securities has time dimensions and the state and outcome of the future are really uncertain. This problem resulting from this uncertainty can be solved by complete market, but it has a weak power to explain real stock market. Capital Market is faced with the uncertainity because it is a kind of incomplete market. Individuals and firms in capital market made their consumption-investment decision by their own criteria, i. e. the maximization of expected utility form intertemporal consumption and the maximization of the market value of firm. We noted that allocative decisions that had to be made in the economy could be naturally subdivided into two groups. One set of decisions concerned the allocation of first-period resources among consumption $C_i$, investment in risky firms $I_j$, and riskless investment M. The other decisions concern the distribution among individuals of income available in the second period $Y_i(\theta)$. Corresponing to this grouping, the theoretical analysis of efficiency has also been dichotomized. The optimality of the distribution of output in the second period is distributive efficiency" and the optimality of the allocation of first-period resources is 'the efficiency of investment'. We have found in the distributive efficiency that the conditions for attainability is the same as the conditions for market optimality. The necessary and sufficient conditions for attainability or market optimality is that (1) all utility functions are such that -$\frac{{U_i}^'(Y_i)}{{U_i}^"(Y_i)}={\mu}_i+{\lambda}Y_i$-linear risk tolerance function where the coefficients ${\mu}_i$ and $\lambda$ are independent of $Y_i$, and (2) there are homogeneous expectations, i. e. ${\Large f}_i(\theta)={\Large f}(\theta)$ for every i. On the other hand, the efficiency of investment has disagreement about optimal investment level. The investment level for market rule will not generally lead to Pareto-optimal allocation of investment. This suboptimality is caused by (1)the difference of Diamond's decomposable production function and mean-variance valuation model and (2) the selection of exelusive investment or competitive investment. In conclusion, this article has made an analysis of conditions and processes of Pareto-optimal allocation of resources in capital marker and tried to connect with significant issues in modern finance.

• 한국정보통신학회논문지
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• 제20권5호
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• pp.917-922
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• 2016

RF신호로부터 전력을 수집하는 에너지 하베스팅 기술은 센서의 전원 공급 문제를 해결함으로써 네트워크의 수명을 향상시킬 수 있는 방안으로 최근 큰 관심을 받고 있다. 본 논문에서는 무선 정보 및 전력 동시 전송을 위한 효율적인 알고리즘을 제안하고자 한다. 먼저, 에너지 하베스팅 네트워크에서 채널의 probability density function을 이용하여 water-level의 하계값을 찾은 후, 이를 기반으로 파워 할당 해를 도출한다. 또한, 최소 필요 획득 에너지 조건을 효율적으로 만족시켜줄 수 있는 파워 분할 방안을 제안하였다. 시뮬레이션을 통해 제안 방안은 기존 방안에 비해 최소 필요 획득 에너지 조건을 보장하면서 평균 데이터 전송률을 향상시키고, 최적해에 비해서는 10% 미만의 미미한 성능 저하가 있었지만 계산 복잡도를 현저히 줄일 수 있음을 보인다.

• 한국항공우주학회지
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• 제48권9호
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• pp.691-701
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• 2020

본 논문은 전기 추진 수직이착륙 무인기의 형상에 적합하도록 회전익 모드에서 추진시스템이 고장난 상황을 대처하기 위한 컨벡스 최적화 기법 기반의 믹서를 제시한다. 각 모터 및 프로펠러의 고장 영향성을 분석하기 위하여 컨벡스 함수 성질을 이용하여 가용 조종력 집합을 계산하였으며 이를 도시하는 방법을 기술하였다. 조종력 할당을 최적화 문제로 정의하고, 실시간으로 최적해를 구하기 위하여 컨벡스 함수로 문제를 재정의하였다. 컨벡스 최적화 솔버를 사용하여 수직 이착륙 비행 모드의 믹서를 구현하였으며 조종력 할당 기법들의 성능을 가용 조종력 범위 집합으로 비교하였다. 최종적으로 비선형 6자유도 시뮬레이션을 통하여 타기법(의사역행렬 기법, 재분배의사역행렬 기법)과 비교 분석하였다.

• Industrial Engineering and Management Systems
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• 제6권2호
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• pp.136-145
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• 2007

The selection of suppliers and the determination of order quantities to be placed with those suppliers are important decisions in a supply chain. In this research, a non-linear mixed integer programming model is presented to select suppliers and determine the order quantities. The model considers the purchasing cost which takes into account quantity discount, the cost of transportation, the fixed cost for establishing suppliers, the cost for holding inventory, and the cost of receiving poor quality parts. The capacity constraints for suppliers, quality and lead-time requirements for the parts are also taken into account in the model. Since the purchasing cost, which is a decreasing step function of order quantities, introduces discontinuities to the non-linear objective function, it is not easy to employ traditional optimization methods. Thus, a heuristic algorithm, called particle swarm optimization (PSO), is used to find the (near) optimal solution. However, PSO usually generates initial solutions randomly. To improve the PSO solution quality, a heuristic procedure is proposed to find an initial solution based on the average unit cost including transportation, purchasing, inventory, and poor quality part cost. The results show that PSO with the proposed initial solution heuristic provides better solutions than those with PSO algorithm only.

• 전자공학회논문지C
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• 제35C권4호
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• pp.38-49
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• 1998

A fossil power plant can be modeled by a lot of algebraic equations and differential equations. When we simulate a large, complicated fossil power plant by a computer such as workstation or PC, it takes much time until overall equations are completely calculated. Therefore, new processing systems which have high computing speed is ultimately needed for real-time or high-speed(faster than real-time) simulators. This paper presents an enhanced strategy in which high computing power can be provided by parallel processing of DSP processors with communication links. DSP system is designed for general purpose. Parallel DSP system can be easily expanded by just connecting new DSP modules to the system. General urpose DSP modules and a VME interface module was developed. New model and techniques for the task allocation are also presented which take into account the special characteristics of parallel I/O and computation. As a realistic cost function of task allocation, we suggested 'simulation period' which represents the period of simulation output intervals. Based on the development of parallel DSP system and realistic task allocation techniques, we cound achieve good efficiency of parallel processing and faster simulation speed than real-time.

• 품질경영학회지
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• 제47권4호
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• pp.701-711
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• 2019

Purpose: The problem of optimizing redundancy allocation in multi-level systems is considered when each item in a multi-level system has alternative items with the same function. The number of redundancy of multi-level system is allocated to maximize the reliability of the system under path set and cost limitation constraints. Methods: Based on cost limitation and path set constraints, a mathematical model is established to maximize system reliability. Particle swarm optimization is employed for redundant allocation and verified by numerical experiments. Results: Comparing the particle swarm optimization method and the memetic algorithm for the 3 and 4 level systems, the particle swarm optimization method showed better performance for solution quality and search time. Particularly, the particle swarm optimization showed much less than the memetic algorithm for variation of results. Conclusion: The proposed particle swarm optimization considerably shortens the time to search for a feasible solution in MRAP with path set constraints. PS optimization is expected to reduce search time and propose the better solution for various problems related to MRAP.

• Industrial Engineering and Management Systems
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• 제10권1호
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• pp.54-64
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• 2011

The purpose of this study is to optimally allocate the human resources to tasks while minimizing the total daily human resource costs and smoothing the human resource usage. The human resource allocation problem (hRAP) under consideration contains two kinds of special constraints, i.e. operational precedence and skill constraints in addition to the ordinary constraints. To deal with the multiple objectives and the special constraints, first we designed this hRAP as a network problem and then proposed a Pareto multistage decisionbased genetic algorithm (P-mdGA). During the evolutionary process of P-mdGA, a Pareto evaluation procedure called generalized Pareto-based scale-independent fitness function approach is used to evaluate the solutions. Additionally, in order to improve the performance of P-mdGA, we use fuzzy logic controller for fine-tuning of genetic parameters. Finally, in order to demonstrate the applicability and to evaluate the performance of the proposed approach, P-mdGA is applied to solve a case study in a hotel, where the managers usually need helpful automatic support for effectively allocating hotel staff to hotel tasks.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2007년도 학술발표회 논문집
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• pp.2039-2043
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• 2007

Like other major river basin systems in the West of the United States the Platte River Basin are faced with the challenges of allocating more water for plant and animal species. A part of the Central Platte River was designated as critical habitat for the whooping crane in 1978. The water allocation system in the Platte River Basin is dominated by the Prior Appropriation Doctrine, which allocates water according to the priorities based on the date of water use. The Platte River Basin segregated into five subregions for purpose of analysis. 24 years of historic records of monthly flow and all the demands were complied. The simulation of river basin modeling includes physical operation of the system including water allocation by water rights and interstate compact agreements, reservoir operations, and diversion with consumptive use and return flow. MODSIM, a generalized river basin network model, was used for estimating the timing and magnitude of impacts on river flows and diversions associated with water transfers from each region. A total of 20 alternatives were considered, covering transfers from each of the five regions of basin with several options. The result shows that the timing and availability of augmented water at the critical habitat is not only a function of use by junior appropriators, but also of river losses, and timing of return flows.