• Title/Summary/Keyword: penalty approach

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Sensitivity Analysis for Production Planning Problems with Backlogging

  • Lee, In-Soo
    • Journal of the Korean Operations Research and Management Science Society
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    • v.12 no.2
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    • pp.5-20
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    • 1987
  • This paper addresses sensitivity analysis for a deterministic multi-period production and inventory model. The model assumes a piecewise linear cost structure, but permits backlogging of unsatisfied demand. Our approach to sensitivity analysis here can be divided into two basic steps; (1) to find the optimal production policy through a forward dynamic programming algorithm similar to the backward version of Zangwill [1966] and (2) to apply the penalty network approach by the author [1986] in order to derive sensitivity ranges for various model parameters. Computational aspects are discussed and topics of further research are suggested.

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Objects Tracking in Image Sequence by Optimization of a Penalty Function

  • Sakata, Akio;Shimai, Hiroyuki;Hiraoka, Kazuyuki;Mishima, Tadetoshi
    • Proceedings of the IEEK Conference
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    • 2002.07a
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    • pp.200-203
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    • 2002
  • We suggest a novel approach to the tracking of multiple moving objects in image sequence. The tracking of multiple moving objects include some complex problems(crossing (occluding), entering, disappearing, joining, and dividing) for objects identifying. Our method can settle these problems by optimization of a penalty function and movement prediction. It is executable in .eat time processing (more than 30 ㎐) because it is computed by only location data.

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Reduced-order controller design via an iterative LMI method (반복 선형행렬부등식을 이용한 축소차수 제어기 설계)

  • Kim, Seog-Joo;Kwon, Soon-Man;Lee, Jong-Moo;Kim, Chun-Kyung;Cheon, Jong-Min
    • Proceedings of the KIEE Conference
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    • 2004.07d
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    • pp.2242-2244
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    • 2004
  • This paper deals with the design of a reduced-order stabilizing controller for the linear system. The coupled lineal matrix inequality (LMI) problem subject to a rank condition is solved by a sequential semidefinite programming (SDP) approach. The nonconvex rank constraint is incorporated into a strictly linear penalty function, and the computation of the gradient and Hessian function for the Newton method is not required. The penalty factor and related term are updated iteratively. Therefore the overall procedure leads to a successive LMI relaxation method. Extensive numerical experiments illustrate the proposed algorithm.

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Structural Dynamic Optimization of Diesel Generator systems Using Genetic Algorithm(GA) (유전자 알고리즘을 이용한 선박용 디젤발전기 시스템의 동특성 해석 및 최적화)

  • 이영우;성활경
    • Journal of Advanced Marine Engineering and Technology
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    • v.24 no.3
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    • pp.99-105
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    • 2000
  • For multi-body dynamic problems. especially coalescent eigenvalue problems with multiobjective optimization, the design sensitivity analysis is too much complicated mathematically and numerically. Therefore, this article proposes a new technique for structural dynamic modification using a mode modification and homologous structures design method with Genetic Algorithm(GA). In this work, the homologous structure of the resiliently mounted multi-body for marine diesel generator systems is studied and the problem is treated as a combinational optimization problem using the GA. In GA formulation, fitness is defined based on penalty function approach. That include homology, allowable stress and minimum weight of common plate.

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Structural Dynamic Optimization Using a Genetic Algorithm(GA) (유전자 알고리즘(GA)을 이용한 구조물의 동적해석 및 최적화)

  • 이영우;성활경
    • Journal of the Korean Society for Precision Engineering
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    • v.17 no.5
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    • pp.93-99
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    • 2000
  • In many dynamic structural optimization problems, the goal is to reduce the total weight of the structure without causing the resonance. Up to now, gradient informations(i.e., design sensitivity) have been used to achieve the goal. For some class of dynamic problems, especially coalescent eigenvalue Problems with multiobjective optimization, the design sensitivity analysis is too much complicated mathematically and numerically. Therefore, this article proposes a new technique fur structural dynamic modification using a mode modification method with Genetic Algorithm(GA). In GA formulation, fitness is defined based on penalty function approach. Design variables are iteratively improved by using genetic algorithm. Two numerical examples are shown, (ⅰ) a cantilevered plate, and (ⅱ) H-shaped structure. The results demonstrate that the proposed method is highly efficient.

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Multi-Objective Controller Design using a Rank-Constrained Linear Matrix Inequality Method (계수조건부 LMI를 이용한 다목적 제어기 설계)

  • Kim, Seog-Joo;Kim, Jong-Moon;Cheon, Jong-Min;Kwon, Soon-Mam
    • Journal of Institute of Control, Robotics and Systems
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    • v.15 no.1
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    • pp.67-71
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    • 2009
  • This paper presents a rank-constrained linear matrix inequality (LMI) approach to the design of a multi-objective controller such as $H_2/H_{\infty}$ control. Multi-objective control is formulated as an LMI optimization problem with a nonconvex rank condition, which is imposed on the controller gain matirx not Lyapunov matrices. With this rank-constrained formulation, we can expect to reduce conservatism because we can use separate Lyapunov matrices for different control objectives. An iterative penalty method is applied to solve this rank-constrained LMI optimization problem. Numerical experiments are performed to illustrate the proposed method.

H-likelihood approach for variable selection in gamma frailty models

  • Ha, Il-Do;Cho, Geon-Ho
    • Journal of the Korean Data and Information Science Society
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    • v.23 no.1
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    • pp.199-207
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    • 2012
  • Recently, variable selection methods using penalized likelihood with a shrink penalty function have been widely studied in various statistical models including generalized linear models and survival models. In particular, they select important variables and estimate coefficients of covariates simultaneously. In this paper, we develop a penalize h-likelihood method for variable selection in gamma frailty models. For this we use the smoothly clipped absolute deviation (SCAD) penalty function, which satisfies a good property in variable selection. The proposed method is illustrated using simulation study and a practical data set.

Structured Controller Synthesis Using a Penalized LMI Method (페널티화된 LMI를 이용한 구조적 제약이 있는 제어기 설계)

  • Kim Seog-Joo;KWon Soonman Kwon;Cheon Jong-Min;Moon Young-Hyun
    • Journal of Institute of Control, Robotics and Systems
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    • v.11 no.8
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    • pp.656-661
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    • 2005
  • This paper is concerned with an iterative linear matrix inequality (LMI) approach to the design of a structurally constrained output feedback controller such as decentralized control. The structured synthesis is formulated as a novel rank-constrained LMI optimization problem, where the controller parameters are explicitly described so as to impose structural constraints on the parameter matrices. An iterative penalty method is applied to solve the rank-constrained LMI problem. Numerical experiments are performed to illustrate the effectiveness of the proposed method.

An Analysis on the Strategic Behaviors of the Bilaterally Monopolistic Firms under Uncertain Information

  • Jun, Iksu
    • Journal of agriculture & life science
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    • v.46 no.6
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    • pp.185-195
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    • 2012
  • The purpose of this paper is to analyze how strategically the bilaterally monopolistic firms, only-one-seller and only-one-buyer, behave in a situation in which each firm has uncertain information on its opponent firm's cost. Even though the two firms know that seeking integrated profit leads to the optimized profit for both firms, each firm has an incentive to opportunistically behave to increase its share of the integrated profit. These opportunistic behaviors of the firms are analyzed through a game theoretic approach especially finding Nash equilibrium mixed strategies for the strategic profiles such as true-report or not and monitoring or not. The comparative statics to the Nash equilibrium mixed strategies shows that as the profit share increases the probability of monitoring an opponent firm is decreased while the probability increases as the size of the overstated production cost increases. This study also shows that high penalty and low monitoring cost lead to high probability to tell the truth of the production cost.

Finite strip method in probabilistic fatigue analysis of steel bridges

  • Li, W.C.;Cheung, M.S.
    • Steel and Composite Structures
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    • v.2 no.6
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    • pp.429-440
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    • 2002
  • A finite strip method is developed for fatigue reliability analysis of steel highway bridges. Flat shell strips are employed to model concrete slab and steel girders, while a connection strip is formed using penalty function method to take into account eccentricity of girder top flange. At each sampling point with given slab thickness and modulus ratio, a finite strip analysis of the bridge under fatigue truck is performed to calculate stress ranges at fatigue-prone detail, and fatigue failure probability is evaluated following the AASHTO approach or the LEFM approach. After the failure probability is integrated over all sampling points, fatigue reliability of the bridge is determined.