• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.844-847
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• 1997

In this paper, scheduling problem is dealt for the minimization of due date penalty for the customer order. Multiproduct batch processes have been dealt with for their suitability for high value added low volume products. Their scheduling problems take minimization of process operation for objective function, which is not enough to meet the customer satisfaction and the process efficiency simultaneously because of increasing requirement of fast adaptation for rapid changing market condition. So new target function has been suggested by other researches to meet two goals. Penalty function minimization is one of them. To present more precisely production scheduling, we develop new scheduling model with penalty function of earliness and tardiness We can find many real cases that penalty parameters are divergent by the difference between the completion time of operation and due date. That is to say, the penalty parameter values for the product change by the customer demand condition. If the order charges different value for due date, we can solve it with the due date period. The period means the time scope where penalty parameter value is 0. If we make use of the due date period, the optimal sequence of our model is not always same with that of fixed due date point. And if every product have due date period, due date of them are overlapped which needs optimization for the maximum profit and minimum penalty. Due date period extension can be enlarged to makespan minimization if every product has the same abundant due date period and same penalty parameter. We solve this new scheduling model by simulated annealing method. We also develop the program, which can calculate the optimal sequence and display the Gantt chart showing the unit progress and time allocation only with processing data.

• Communications for Statistical Applications and Methods
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• v.24 no.6
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• pp.651-662
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• 2017

We propose an alternative procedure to select penalty parameter in $L_1$ penalized robust regression. This procedure is based on marginalization of prior distribution over the penalty parameter. Thus, resulting objective function does not include the penalty parameter due to marginalizing it out. In addition, its estimating algorithm automatically chooses a penalty parameter using the previous estimate of regression coefficients. The proposed approach bypasses cross validation as well as saves computing time. Variable-wise penalization also performs best in prediction and variable selection perspectives. Numerical studies using simulation data demonstrate the performance of our proposals. The proposed methods are applied to Boston housing data. Through simulation study and real data application we demonstrate that our proposals are competitive to or much better than cross-validation in prediction, variable selection, and computing time perspectives.

• Journal of the Korean Data and Information Science Society
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• v.23 no.6
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• pp.1289-1297
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• 2012

We consider a general compound Poisson risk model in which the premium rate is surplus dependent. We analyze the joint distribution of the surplus immediately before ruin, the deffcit at ruin and the time of ruin by solving the integro-differential equation for the Gerber-Shiu discounted penalty function.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.13-18
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• 2003

This paper proposes a design method of PID controllers in the framework of a constrained optimization problem. Owing to the popularity for the controller's simplicity and robustness, a great deal of literature concerning PID control design has been published, which can be classified into frequency-based and time-based approaches. However, both approaches have to be considered together for a designed PID control to work well with a guaranteed closed-loop stability. For this purpose, a penalty function is formulated to satisfy both frequency- and time-domain specifications, and is minimized by a recet nonlinear optimization algorithm to attain optimal PID control gains. The proposed method is compared with Wang's and Ho's methods on a suite of example systems. Simulation results show that the PID control tuned by the proposed method improves time-domain performance without deteriorating closed-loop stability.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.1
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• pp.85-90
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• 2013

PID control for unstable processes with time delay is not easy to apply because of unstability due to the poles existing on left-hand side in s-plane and the effect of time delay. In this paper, the authors consider the PID controller design technique in case of predefining overshoot or rising time by designer according to control environment. To deal with constraint problem like this, in this paper, the RCGA incorporating the penalty strategy is used. This is the method that if the RCGA violates given constraints, the defined penalty function is summed to the evaluation function depending on the severity and then the given constraint problem is converted to non-constraints optimization problem. The proposed method is applied to the unstable FOPTD(First Order Plus Time Delay) system and simulations are accomplished to illustrate the set-point tracking performance.

• The Journal of the Acoustical Society of Korea
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• v.43 no.3
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• pp.314-323
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• 2024

Recently, a score-penalty method has been used for the acoustic passive tracking of marine mammals. The interesting aspect of this technique lies in the loss function, which has a penalty term representing the mismatch between the measured signal and the modeled signal, while the traditional time-domain matched-field processing is positively considering the match between them. In this study, we apply the score-penalty method into the depth estimation of a passive target with a known source waveform. Assuming deep ocean environments with uncertainties in the sound speed profile, we evaluate the score-penalty method, comparing it with the time-domain matched field processing method. We shows that the score-penalty method is more accurate than the time-domain matched field processing method in the ocean environment with weak mismatch of sound speed profile, and has better efficiency. However, in the ocean enviroment with strong mismatch of the sound speed profile, the score-penalty method also fails in the depth estimation of a target, similar to the time-domain matched-field processing method.

• Journal of Information Processing Systems
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• v.17 no.2
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• pp.306-317
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• 2021

The unbalance between system ergodic sum rate and high fairness is one of the key issues affecting the performance of non-orthogonal multiple access (NOMA) system. To solve the problem, this paper proposes a power allocation algorithm to realize the ergodic sum rate maximization of NOMA system. The scheme is mainly achieved by the construction algorithm of fair model based on α fair utility function and the optimal solution algorithm based on the interior point method of penalty function. Aiming at the construction of fair model, the fair target is added to the traditional power allocation model to set the reasonable target function. Simultaneously, the problem of ergodic sum rate and fairness in power allocation is weighed by adjusting the value of α. Aiming at the optimal solution algorithm, the interior point method of penalty function is used to transform the fair objective function with unequal constraints into the unconstrained problem in the feasible domain. Then the optimal solution of the original constrained optimization problem is gradually approximated within the feasible domain. The simulation results show that, compared with NOMA and time division multiple address (TDMA) schemes, the proposed method has larger ergodic sum rate and lower Fairness Index (FI) values.

• 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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.4
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• pp.718-724
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• 2008

We present a novel joint barcode deblurring and nonuniform illumination compensation algorithm for barcode signals whose number of modules is known. The proposed algorithm is based on a penalized least squares method using a roughness penalty function for an illumination model and a double well penalty function for a barcode signal model. In simulations, the proposed method shows an improved performance compared with a conventional method without compensating nonuniform illumination effects. In addition, the proposed method converges quickly during optimization(within 15 iterations), thereby showing strong possibility for real time decoding of barcode signals.

• Journal of Korea Water Resources Association
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• v.45 no.12
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• pp.1213-1226
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• 2012

Evolutionary algorithms, which are frequently used in an automatic calibration of watershed runoff simulation models, are unconstrained optimization algorithms. An additional method is required to impose constraints on those algorithms. The purpose of the study is to modify the SCE-UA (shuffled complex evolution-University of Arizona) to impose constraints by a penalty function and to improve performance of the automatic calibration module of the SWMM (storm water management model) linked with the SCE-UA. As indicators related to peak flow are important in watershed runoff event simulation, error of peak flow and error of peak flow occurrence time are selected to set up constraints. The automatic calibration module including the constraints was applied to the Milyang Dam Basin and the Guro 1 Pumping Station Basin. The automatic calibration results were compared with the results calibrated by an automatic calibration without the constraints. Error of peak flow and error of peak flow occurrence time were greatly improved and the original objective function value is not highly violated in the automatic calibration including the constraints. The automatic calibration model with constraints was also verified, and the results was excellent. In conclusion, the performance of the automatic calibration module for watershed runoff event simulation was improved by application of the penalty function to impose constraints.