• Title/Summary/Keyword: 퍼터베이션 분석

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Mean-shortfall optimization problem with perturbation methods (퍼터베이션 방법을 활용한 평균-숏폴 포트폴리오 최적화)

  • Won, Hayeon;Park, Seyoung
    • The Korean Journal of Applied Statistics
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    • v.34 no.1
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    • pp.39-56
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    • 2021
  • Many researches have been done on portfolio optimization since Markowitz (1952) published a diversified investment model. Markowitz's mean-variance portfolio optimization problem is established under the assumption that the distribution of returns follows a normal distribution. However, in real life, the distribution of returns does not follow a normal distribution, and variance is not a robust statistic as it is heavily influenced by outliers. To overcome these potential issues, mean-shortfall portfolio model was proposed that utilized downside risk, shortfall, as a risk index. In this paper, we propose a perturbation method that uses the shortfall as a risk index of the portfolio. The proposed portfolio utilizes an adaptive Lasso to obtain a sparse and stable asset selection because it can reduce management and transaction costs. The proposed optimization is easily applicable as it can be computed using an efficient linear programming. In our real data analysis, we show the validity of the proposed perturbation method.

Optimal Policy for (s, S) Inventory System by a Sensitivity Analysis through Simulation (시뮬레이션 민감도 분석을 이용한 (s, S) 재고 시스템의 최적전략)

  • 권치명
    • Proceedings of the Korea Society for Simulation Conference
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    • 2003.06a
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    • pp.167-175
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    • 2003
  • 본 연구는 (s, S) 재고시스템의 최적 재고정책을 수립하는 문제를 시뮬레이션을 통하여 분석하고자 한다. 이러한 목적으로 재고관리비용에 대한 파라미터 (s, S)의 민감도를 퍼터베이션 분석법으로 구하고 확률 최적화 기법을 적용하여 단위 기간에 평균 재고관리비용을 최적으로 하는 재고정책을 발견하였다. 민감도의 추정에는 IPA법과 SPA법을 표본경로의 주문 사건 변동에 따라 조건적으로 결합하여 사용하였다. 시뮬레이션 결과 s와 S의 최적정책 추정치를 상당히 정확한 값으로 얻었으며 이러한 결과는 보다 일반적인 재고관리 문제의 분석에 도움을 줄 것으로 기대한다.

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Linear programming models using a Dantzig type risk for portfolio optimization (Dantzig 위험을 사용한 포트폴리오 최적화 선형계획법 모형)

  • Ahn, Dayoung;Park, Seyoung
    • The Korean Journal of Applied Statistics
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    • v.35 no.2
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    • pp.229-250
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    • 2022
  • Since the publication of Markowitz's (1952) mean-variance portfolio model, research on portfolio optimization has been conducted in many fields. The existing mean-variance portfolio model forms a nonlinear convex problem. Applying Dantzig's linear programming method, it was converted to a linear form, which can effectively reduce the algorithm computation time. In this paper, we proposed a Dantzig perturbation portfolio model that can reduce management costs and transaction costs by constructing a portfolio with stable and small (sparse) assets. The average return and risk were adjusted according to the purpose by applying a perturbation method in which a certain part is invested in the existing benchmark and the rest is invested in the assets proposed as a portfolio optimization model. For a covariance estimation, we proposed a Gaussian kernel weight covariance that considers time-dependent weights by reflecting time-series data characteristics. The performance of the proposed model was evaluated by comparing it with the benchmark portfolio with 5 real data sets. Empirical results show that the proposed portfolios provide higher expected returns or lower risks than the benchmark. Further, sparse and stable asset selection was obtained in the proposed portfolios.

Optimization of Queueing Network by Perturbation Analysis (퍼터베이션 분석을 이용한 대기행렬 네트워크의 최적화)

  • 권치명
    • Journal of the Korea Society for Simulation
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    • v.9 no.2
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    • pp.89-102
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    • 2000
  • In this paper, we consider an optimal allocation of constant service efforts in queueing network to maximize the system throughput. For this purpose, using the perturbation analysis, we apply a stochastic optimization algorithm to two types of queueing systems. Our simulation results indicate that the estimates obtained from a stochastic optimization algorithm for a two-tandem queuing network are very accurate, and those for closed loop manufacturing system are a little apart from the known optimal allocation. We find that as simulation time increases for obtaining a new gradient (performance measure with respect to decision variables) by perturbation algorithm, the estimates tend to be more stable. Thus, we consider that it would be more desirable to have more accurate sensitivity of performance measure by enlarging simulation time rather than more searching steps with less accurate sensitivity. We realize that more experiments on various types of systems are needed to identify such a relationship with regards to stopping rule, the size of moving step, and updating period for sensitivity.

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Optimal Policy for (s, S) Inventory System Characterized by Renewal Arrival Process of Demand through Simulation Sensitivity Analysis (수요가 재생 도착과정을 따르는 (s, S) 재고 시스템에서 시뮬레이션 민감도 분석을 이용한 최적 전략)

  • 권치명
    • Journal of the Korea Society for Simulation
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    • v.12 no.3
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    • pp.31-40
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    • 2003
  • This paper studies an optimal policy for a certain class of (s, S) inventory control systems, where the demands are characterized by the renewal arrival process. To minimize the average cost over a simulation period, we apply a stochastic optimization algorithm which uses the gradients of parameters, s and S. We obtain the gradients of objective function with respect to ordering amount S and reorder point s via a combined perturbation method. This method uses the infinitesimal perturbation analysis and the smoothed perturbation analysis alternatively according to occurrences of ordering event changes. The optimal estimates of s and S from our simulation results are quite accurate. We consider that this may be due to the estimated gradients of little noise from the regenerative system simulation, and their effect on search procedure when we apply the stochastic optimization algorithm. The directions for future study stemming from this research pertain to extension to the more general inventory system with regard to demand distribution, backlogging policy, lead time, and inter-arrival times of demands. Another direction involves the efficiency of stochastic optimization algorithm related to searching procedure for an improving point of (s, S).

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Modal Analysis of Rectangular MQW Waveguide : A Novel Approach using Scanning Angle Method (직사각형 다중 양자 우물 도파관의 모드특성 분석 : Scanning angle method를 사용한 새로운 접근)

  • Im, Yeon-Seop;Choe, Yeong-Wan
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.37 no.4
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    • pp.45-52
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    • 2000
  • We present a novel method for simple and efficient analysis of the rectangular MQW waveguide. Preferentially two-dimensional structure is transformed into one-dimensional structure by using the effective index method. Then, the characteristic matrix of the resultant planar MQW waveguide is analyzed by scanning angle method. The effective index, modal intensity, and optical confinement factor of rectangular MQW waveguide can be effectively obtained by this method. Our simulation results show excellent agreement with the accurate solutions based on the finite element method. We also introduce the approximation methods for the analysis of rectangular MQW waveguide and investigate their validity. By using perturbation approach, modal power loss of guided wave in rectangular MQW waveguide is newly investigated and compared with the conventional method using the approximation of planar MQW waveguide.

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