• 제목/요약/키워드: Lagrangian multiplier

검색결과 51건 처리시간 0.027초

Modified Lagrangian 신경망을 이용한 경제 급전 (Economic Load Dispatch Using Modified Lagrangian ANN)

  • 김용환;이승철
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1996년도 추계학술대회 논문집 학회본부
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    • pp.133-136
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    • 1996
  • In the paper, an artificial neural network (ANN) approach based on Lagrange multiplier method (Lagrangian ANN) is used to solve an economic load dispatch (ELD) problem. Traditionally ELD problem has one convex cost function as its objective function and nonlinear constraints such as power balance and maximum-minimum limits of real power. In this study, modification is given to the Lagrangian ANN proposed by Gong et all[5] to guarantee the convergence to the optimal solution. Simulation results demonstrate the effectiveness of the proposed method applied to the ELD problem.

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A Lagrangian Relaxation Approach to Capacity Planning for a Manufacturing System with Flexible and Dedicated Machines

  • Lim, Seung-Kil;Kim, Yeong-Dae
    • 한국경영과학회지
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    • 제23권2호
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    • pp.47-65
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    • 1998
  • We consider a multiperiod capacity planning problem for determining a mix of flexible and dedicated capacities under budget restriction. These capacities are controlled by purchasing flexible machines and/or new dedicated machines and disposing old dedicated machines. Acquisition and replacement schedules are determined and operations are assigned to the flexible or dedicated machines for the objective of minimizing the sum of discounted costs of acquisition and operation of flexible machines, new dedicated machines, and old dedicated machines. In this research, the Problem is formulated as a mixed integer linear Program and solved by a Lagrangian relaxation approach. A subgradient optimization method is employed to obtain lower bounds and a multiplier adjustment method is devised to improve the bounds. We develop a linear programming based Lagrangian heuristic algorithm to find a good feasible solution of the original problem. Results of tests on randomly generated test problems show that the algorithm gives relatively good solutions in a reasonable amount of computation time.

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A MW-Mvar Investment Technique Focused on System Loss Minimization

  • Eom, Jae-Sun;Lee, Sang-Joong;Kim, Kern-Jong
    • Journal of KIEE
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    • 제11권1호
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    • pp.51-54
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    • 2001
  • In this paper, a MW-Mvar investment technique focused on minimizing the system loss is presented. An optimization technique, in which the system loss is defined as the objective function and the power flow equations as the constraints, is introduced to obtain the Lagrangian multipliers λP and λQ. The Lagrangian multipliers imply the variation of the system loss with respect to incremental bus power and are used as MW-Mvar investment indices for minimizing the system loss. ΔP MW and ΔQ Mvar are invested, step by step, by the priority of λP and λQ index given for each bus. Derivation of the index uses the information from normal power flow calculation.

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A Least Squares Iterative Method For Solving Nonlinear Programming Problems With Equality Constraints

  • Sok Yong U.
    • 한국국방경영분석학회지
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    • 제13권1호
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    • pp.91-100
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    • 1987
  • This paper deals with an algorithm for solving nonlinear programming problems with equality constraints. Nonlinear programming problems are transformed into a square sums of nonlinear functions by the Lagrangian multiplier method. And an iteration method minimizing this square sums is suggested and then an algorithm is proposed. Also theoretical basis of the algorithm is presented.

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Laguerre Polynomial을 이용한 저수지군의 최적제어 (Optimal Control of Multireservoirs Using Discrete Laguerre Polynomials)

  • 이재형;김민환
    • 대한토목학회논문집
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    • 제11권4호
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    • pp.91-102
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    • 1991
  • 저수지군을 최적으로 운영하려고 할때 일반적으로 동적계획법을 이용하는데 저수지 수의 증가와 변수의 이산화에 따라 계산 용량이 지수적으로 팽창하는 결점을 내포하고 있다. 이 문제를 해결하기 위해서 본 논문에서는 저수지 시스템 변수가 LP(Laguerre Polynomial)로 표현된 새로운 모형 개발을 시도하였다. 새로운 계획모형은 QP(Quadratic Programming) 형태이다. 이 모형의 해는 확장 라그란지안 곱수 방법(Augmented Lagrangian Multiplier Method)의 비선형계획법에 의해서 QP해를 구하였다. 그 결과 저수 수준은 기존의 결과보다 높게 유지하려는 경향을 보였으며, 평가된 편익 값은 다른 방법들과 비슷한 값이었다.

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미세유로를 갖는 납작관의 열·유동 해석 (Thermal and Flow Analysis of the Flat Tube with Micro-Channels)

  • 정길완;이관수;김우승
    • 대한기계학회논문집B
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    • 제23권8호
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    • pp.978-986
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    • 1999
  • In this study, the general thermal and flow characteristics of flat tube with micro-channels has been studied and the correlation of Nusselt number and friction factor is proposed. The optimal flat tube geometry is determined by optimal design process. It is assumed to be a three dimensional laminar flow in the analysis of thermal and flow characteristics. The periodic boundary condition is applied since the geometry of flat tube with micro-channels shows uniform cross-section in primary flow direction. Local Nusselt number is examined for thermal characteristics of each membrane, and module average Nusselt number and friction factor are calculated to determine the characteristics of the heat transfer and pressure drop in overall flat tube with microchannels. The correlations between Nusselt number and friction factor are given by Reynolds number, aspect ratio of membranes, and the width of flat tube. ALM (Augmented Lagrangian Multiplier) method is applied to the correlations to determine an optimal shape of flat tube. It is shown that the optimal aspect ratio of flat tube is approximately 1.0, irrespective of the width of flat tube and Reynolds number.

CONFLICT AMONG THE SHRINKAGE ESTIMATORS INDUCED BY W, LR AND LM TESTS UNDER A STUDENT'S t REGRESSION MODEL

  • Kibria, B.M.-Golam
    • Journal of the Korean Statistical Society
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    • 제33권4호
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    • pp.411-433
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    • 2004
  • The shrinkage preliminary test ridge regression estimators (SPTRRE) based on Wald (W), Likelihood Ratio (LR) and Lagrangian Multiplier (LM) tests for estimating the regression parameters of the multiple linear regression model with multivariate Student's t error distribution are considered in this paper. The quadratic biases and risks of the proposed estimators are compared under both null and alternative hypotheses. It is observed that there is conflict among the three estimators with respect to their risks because of certain inequalities that exist among the test statistics. In the neighborhood of the restriction, the SPTRRE based on LM test has the smallest risk followed by the estimators based on LR and W tests. However, the SPTRRE based on W test performs the best followed by the LR and LM based estimators when the parameters move away from the subspace of the restrictions. Some tables for the maximum and minimum guaranteed efficiency of the proposed estimators have been given, which allow us to determine the optimum level of significance corresponding to the optimum estimator among proposed estimators. It is evident that in the choice of the smallest significance level to yield the best estimator the SPTRRE based on Wald test dominates the other two estimators.

Energy-Efficient Resource Allocation for Application Including Dependent Tasks in Mobile Edge Computing

  • Li, Yang;Xu, Gaochao;Ge, Jiaqi;Liu, Peng;Fu, Xiaodong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제14권6호
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    • pp.2422-2443
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    • 2020
  • This paper studies a single-user Mobile Edge Computing (MEC) system where mobile device (MD) includes an application consisting of multiple computation components or tasks with dependencies. MD can offload part of each computation-intensive latency-sensitive task to the AP integrated with MEC server. In order to accomplish the application faultlessly, we calculate out the optimal task offloading strategy in a time-division manner for a predetermined execution order under the constraints of limited computation and communication resources. The problem is formulated as an optimization problem that can minimize the energy consumption of mobile device while satisfying the constraints of computation tasks and mobile device resources. The optimization problem is equivalently transformed into solving a nonlinear equation with a linear inequality constraint by leveraging the Lagrange Multiplier method. And the proposed dual Bi-Section Search algorithm Bi-JOTD can efficiently solve the nonlinear equation. In the outer Bi-Section Search, the proposed algorithm searches for the optimal Lagrangian multiplier variable between the lower and upper boundaries. The inner Bi-Section Search achieves the Lagrangian multiplier vector corresponding to a given variable receiving from the outer layer. Numerical results demonstrate that the proposed algorithm has significant performance improvement than other baselines. The novel scheme not only reduces the difficulty of problem solving, but also obtains less energy consumption and better performance.

H.264를 위한 적응적인 비트-왜곡 최적화 방법 (An Adaptive Rate-Distortion Optimization Method for H.264 Video Codec)

  • 오관정;호요성
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2005년도 추계종합학술대회
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    • pp.323-326
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    • 2005
  • Several video coding standards, such as MPEG-4 and H.263, have been investigated to reduce the resulting number of bits while pursuing the maximum video quality. The recent video coding standard, H.264, provides higher coding efficiency than previous coding standards by using the mode decision scheme. For mode decision, H.264 chooses the best macroblock mode among the several candidates using Lagrangian cost function which reflects both the rate and the distortion. H.264 employs only one rate-distortion optimization (RDO) model for all macroblocks. Since the characteristics of each macroblock is different, each macroblock should have its own RDO model. In this paper, we propose an adaptive rate-distortion optimization algorithm for H.264. We regulate the Lagrangian multiplier considering the picture type and characteristics of each macroblock.

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근사 선탐색을 이용한 동적 반응 최적화 (Dynamic response optmization using approximate search)

  • 김민수;최동훈
    • 대한기계학회논문집A
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    • 제22권4호
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    • pp.811-825
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    • 1998
  • An approximate line search is presented for dynamic response optimization with Augmented Lagrange Multiplier(ALM) method. This study empolys the approximate a augmented Lagrangian, which can improve the efficiency of the ALM method, while maintaining the global convergence of the ALM method. Although the approximate augmented Lagragian is composed of only the linearized cost and constraint functions, the quality of this approximation should be good since an approximate penalty term is found to have almost second-order accuracy near the optimum. Typical unconstrained optimization algorithms such as quasi-Newton and conjugate gradient methods are directly used to find exact search directions and a golden section method followed by a cubic polynomial approximation is empolyed for approximate line search since the approximate augmented Lagrangian is a nonlinear function of design variable vector. The numberical performance of the proposed approach is investigated by solving three typical dynamic response optimization problems and comparing the results with those in the literature. This comparison shows that the suggested approach is robust and efficient.