• Title/Summary/Keyword: Optimal Model

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Optimal design of batch-storage serial trains considering setup and inventory holding cost (준비비와 재고비를 고려한 직렬 비연속 공정과 중간 저장조의 최적설계)

  • Lee, Gyeong-Beom
    • Journal of Institute of Control, Robotics and Systems
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    • v.3 no.4
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    • pp.398-405
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    • 1997
  • This article presents a new model which is called Periodic Square-Wave(PSW) to describe the material flow of the periodic processes involving intermediate buffer. The material flows incoming into and outgoing from the intermediate buffer are assumed to be periodic square shaped. PSW model gives the same result as that of Economic Production Quantity(EPQ) model for determining optimal lot size of single stage batch storage system. However, for batch storage serial train system, PSW model gives a different optimal solution of about 6 % reduced total cost. PSW model provides the more accurate information on inventory and production system than the classical approach by maintaining simplicity and increasing computational burden.

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Approximate Optimization of High-speed Train Shape and Tunnel Condition to Reduce the Micro-pressure Wave (미기압파 저감을 위한 고속전철 열차-터널 조건의 근사최적설계)

  • Kim, Jung-Hui;Lee, Jong-Soo;Kwon, Hyeok-Bin
    • Proceedings of the KSME Conference
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    • 2004.04a
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    • pp.1023-1028
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    • 2004
  • A micro-pressure wave is generated by the high-speed train which enters a tunnel, and it causes explosive noise and vibration at the exit. It is known that train speed, train-tunnel area ratio, nose slenderness and nose shape mainly influence on generating micro-pressure wave. So it is required to minimize it by searching optimal values of such train shape factors and tunnel condition. In this study, response surface model, one of approximation models, is used to perform optimization effectively and analyze sensitivity of design variables. Owen's randomized orthogonal array and D-optimal Design are used to construct response surface model. In order to increase accuracy of model, stepwise regression is selected. Finally SQP(Sequential Quadratic Programming) optimization algorithm is used to minimize the maximum micro-pressure wave by using built approximation model.

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An Adaptive Optimization Algorithm Based on Kriging Interpolation with Spherical Model and its Application to Optimal Design of Switched Reluctance Motor

  • Xia, Bin;Ren, Ziyan;Zhang, Yanli;Koh, Chang-Seop
    • Journal of Electrical Engineering and Technology
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    • v.9 no.5
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    • pp.1544-1550
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    • 2014
  • In this paper, an adaptive optimization strategy utilizing Kriging model and genetic algorithm is proposed for the optimal design of electromagnetic devices. The ordinary Kriging assisted by the spherical covariance model is used to construct surrogate models. In order to improve the computational efficiency, the adaptive uniform sampling strategy is applied to generate sampling points in design space. Through several iterations and gradual refinement process, the global optimal point can be found by genetic algorithm. The proposed algorithm is validated by application to the optimal design of a switched reluctance motor, where the stator pole face and shape of pole shoe attached to the lateral face of the rotor pole are optimized to reduce the torque ripple.

OPTIMAL PORTFOLIO CHOICE IN A BINOMIAL-TREE AND ITS CONVERGENCE

  • Jeong, Seungwon;Ahn, Sang Jin;Koo, Hyeng Keun;Ahn, Seryoong
    • East Asian mathematical journal
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    • v.38 no.3
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    • pp.277-292
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    • 2022
  • This study investigates the convergence of the optimal consumption and investment policies in a binomial-tree model to those in the continuous-time model of Merton (1969). We provide the convergence in explicit form and show that the convergence rate is of order ∆t, which is the length of time between consecutive time points. We also show by numerical solutions with realistic parameter values that the optimal policies in the binomial-tree model do not differ significantly from those in the continuous-time model for long-term portfolio management with a horizon over 30 years if rebalancing is done every 6 months.

Optimal Route Planning for Maritime Autonomous Surface Ships Using a Nonlinear Model Predictive Control

  • Daejeong Kim;Zhang Ming;Jeongbin Yim
    • Journal of Navigation and Port Research
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    • v.47 no.2
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    • pp.66-74
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    • 2023
  • With the increase of interest in developing Maritime Autonomous Surface Ships (MASS), an optimal ship route planning is gradually gaining popularity as one of the important subsystems for autonomy of modern marine vessels. In the present paper, an optimal ship route planning model for MASS is proposed using a nonlinear MPC approach together with a nonlinear MMG model. Results drawn from this study demonstrated that the optimization problem for the ship route was successfully solved with satisfaction of the nonlinear dynamics of the ship and all constraints for the state and manipulated variables using the nonlinear MPC approach. Given that a route generation system capable of accounting for nonlinear dynamics of the ship and equality/inequality constraints is essential for achieving fully autonomous navigation at sea, it is expected that this paper will contribute to the field of autonomous vehicles by demonstrating the performance of the proposed optimal ship route planning model.

A New Model and Optimal Pole-Placement Control for the Suspension System of Macpherson Type (Macpherson형 현가장치의 새로운 모델링과 최적극배치 제어)

  • 홍금식;전동섭;김철민;유완석
    • Journal of Institute of Control, Robotics and Systems
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    • v.4 no.6
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    • pp.713-721
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    • 1998
  • In this paper a new modeling and an optimal pole-placement control for the suspension system of Macpherson type are investigated. The rotational motion of the unsprung mass is emphasized in the new modeling. The two generalized coordinates selected in the new model are the vortical displacement of sprung mass and the angular displacement of control arm. Both variables are measured from their static equilibrium points. It is shown that the conventional model is a special case of the new model since the transfer function of the new model coincides with that of the conventional one if the lower support point of the shock absorber is located at the mass center of the unsprung mass. It is also shown that the resonance frequencies of the new model agree better with experimental results. Therefore, the new model is more general in the sense that it Provides an extra degree of freedom in determining the plant model for control system design. An optimal pole-placement control which combines LQ control and pole-placement technique is applied to the new model. Simulations are provided.

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Optimal Bayesian MCMC based fire brigade non-suppression probability model considering uncertainty of parameters

  • Kim, Sunghyun;Lee, Sungsu
    • Nuclear Engineering and Technology
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    • v.54 no.8
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    • pp.2941-2959
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    • 2022
  • The fire brigade non-suppression probability model is a major factor that should be considered in evaluating fire-induced risk through fire probabilistic risk assessment (PRA), and also uncertainty is a critical consideration in support of risk-informed performance-based (RIPB) fire protection decision-making. This study developed an optimal integrated probabilistic fire brigade non-suppression model considering uncertainty of parameters based on the Bayesian Markov Chain Monte Carlo (MCMC) approach on electrical fire which is one of the most risk significant contributors. The result shows that the log-normal probability model with a location parameter (µ) of 2.063 and a scale parameter (σ) of 1.879 is best fitting to the actual fire experience data. It gives optimal model adequacy performance with Bayesian information criterion (BIC) of -1601.766, residual sum of squares (RSS) of 2.51E-04, and mean squared error (MSE) of 2.08E-06. This optimal log-normal model shows the better performance of the model adequacy than the exponential probability model suggested in the current fire PRA methodology, with a decrease of 17.3% in BIC, 85.3% in RSS, and 85.3% in MSE. The outcomes of this study are expected to contribute to the improvement and securement of fire PRA realism in the support of decision-making for RIPB fire protection programs.

Improvement of Optimal Bus Scheduling Model Reflecting Bus Passenger's Degree of Satisfaction (이용자 만족도를 반영한 최적 버스 배차 간격 설정 모형의 개발)

  • Bae, Sang-Hoon;Kim, Tag-Young;Ryu, Byung-Yong
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.6 no.3
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    • pp.12-23
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    • 2007
  • The purpose of this studγ if to understand problem of present bus scheduling system and to develop optimal bus scheduling model which improve bus passenger's degree of satisfaction(DOS) and bus company's operation efficiency at the same time. This study developed optimal bus scheduling model, which reflected bus passenger's degree of satisfaction(DOS), applied to existing model that summery of bus operation cost($C_o$), passenger queuing time cost($C_{pw}$) and passenger travel time cost($C_{pl}$). And optimal bus scheduling model which developed in this study is optimized that using LINGO program based on linear program. Also by using the general case in Busan, compare total cost of present bus scheduling system and existing scheduling model with total cost of optimal bus scheduling model which reflected bus passenger's degree of satisfaction(DOS).

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A study on time optimal positioning control of robotic manipulator (로보트 팔의 최소시간 위치제어에 관한 연구)

  • 김종찬;배준경;박종국
    • 제어로봇시스템학회:학술대회논문집
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    • 1986.10a
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    • pp.45-48
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    • 1986
  • In this paper, time optimal positioning control of the robotic manipulator is discussed. The equations for dynamic model of the robotic manipulator are nonolinear, and each link is highly coupled. A feedback linearizing and decoupling transformation makes the dynamic model linearized and decoupled, and optimal control input for the linear and decoupled system is derived.

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The Optimal Timing of Markdowns: A Decision Model for Jean Market (가격인하 최적시기 연구: Jean Market을 대상으로 한 Decision Model를 중심으로)

  • 곽영식;김용준;남용식;이진화
    • Journal of the Korean Society of Clothing and Textiles
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    • v.26 no.5
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    • pp.606-617
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    • 2002
  • The purpose of this study is to develop a decision model that helps manufacturers and retailers determine the optimal timing of markdown in order to maximize their profit. An optimal timing decision model was developed based on three steps; conjoint measurement, scenario analysis and simulation. Data were collected from the sample of 149 out of 170 undergraduate and graduate students in Seoul in 1997. From the Jeans market, 8 brands; Levi's, lee, Guess, Calvin Klein, Pintos, Get used, MFG, and Basic, were selected as competitors for this study. In the conjoint measurement, respondents estimated the level of preference, from 1 to 100, for each item in which brand, price, style, and colors were used to explain product characteristics. Then, in order to reflect competitive situation in Jeans market, four types of scenarios were developed. In each scenario, simulations were applied to decide optimal timing of markdowns that leads to maximal profitability and sales volume. The profit was calculated based on the equation; Profit = Jean's market volume x market share of each brand - cost, where market volume was obtained by integral calculus for market utility function, and market share by logit value of part-worth from the conjoint analysis. For the purpose of the parsimony of the research, costs and the level of markdown were fixed to 30% of the regular price. In results, the optimal timing decision model identified 3 different types of brands. The brands that do not need to take markdown were Ievi's, MFG, and Basic Jeans characterized by the highest brand power and the highest price zone. The brands that needed to take early markdowns were Guess, Lee, Calvin Klein, and Get Used with the intermediate level of brand power and price. The brand that need late markdown was Pintos with the weakest brand power among the competitors and the lowest price. The optimal range of markdown remains for further research.