• 한국경영과학회지
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• 제13권1호
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• pp.10-23
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• 1988

This paper examines a deterministic, discrete-time, finite-horizon, production/distribution problem for a one-plant multi-retailer system. Production may occur at the plant in each time period. Customer demands at each retailer over a finite number of periods are known and must be met without backlogging. The plant as well as the retailers can serve as stocking points. The problem is to find a minimum-cost production/distribution schedule satisfying the known demands. We show that under a certain cost structure a nested policy is optimal, and present an efficient algorithm to find such an optimal policy. Planning horizon results and some computational saving schemes are also presented.

• 한국경영과학회지
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• 제25권4호
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• pp.111-122
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• 2000

This paper considers remanufacturing planning problems under deterministic environments. As increasing the environmental pressures in manufacturing, various methods for reducing wasted or postponing the time to be waste are considered. This paper considers remanufacturing planning problems on a single facility, where the wastes(or used products) are remanufactured to satisfy the given demand on the remanufactured products. The objective is to find the optimal remanufacturing and purchasing planning of the wastes which minimize total cost subject to satisfaction all the given demand on the remanufactured products. Two problems that the amount of wastes is a given constant or a decision variable are considered, respectively. For the problems, the extreme point solutions are characterized, and dynamic programming algorithms are developed with numerical examples.

• 수산해양기술연구
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• 제32권4호
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• pp.432-446
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• 1996

A stochastic Hamilton variational principle(SHVP) is formulated for dynamic problems of linear continuum. The SHVP allows incorporation of probabilistic distributions into the finite element analysis. The formulation is simplified by transformation of correlated random variables to a set of uncorrelated random variables through a standard eigenproblem. A procedure based on the Fourier analysis and synthesis is presented for eliminating secularities from the perturbation approach. In addition to, a method to analyse stochastic design sensitivity for structural dynamics is present. A combination of the adjoint variable approach and the second order perturbation method is used in the finite element codes. An alternative form of the constraint functional that holds for all times is introduced to consider the time response of dynamic sensitivity. The algorithms developed can readily be adapted to existing deterministic finite element codes. The numerical results for stochastic analysis by proceeding approach of cantilever, 2D-frame and 3D-frame illustrates in this paper.

• Structural Monitoring and Maintenance
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• 제1권4호
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• pp.427-449
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• 2014

A hybrid optimization method for the identification of state-space models is presented in this study. Hybridization is succeeded by combining the advantages of deterministic and stochastic algorithms in a superior scheme that promises faster convergence rate and reliability in the search for the global optimum. The proposed hybrid algorithm is developed by replacing the original stochastic mutation operator of Evolution Strategies (ES) by the Levenberg-Marquardt (LM) quasi-Newton algorithm. This substitution results in a scheme where the entire population cloud is involved in the search for the global optimum, while single individuals are involved in the local search, undertaken by the LM method. The novel hybrid identification framework is assessed through the Monte Carlo analysis of a simulated system and an experimental case study on a shear frame structure. Comparisons to subspace identification, as well as to conventional, self-adaptive ES provide significant indication of superior performance.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2006년도 추계학술대회
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• pp.693-696
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• 2006

Global optimization is a method for finding more reliable models in various fields, such as financial engineering, pattern recognition, process optimization. In this study, we compare and analyze the performance of the state-of-the-art global optimization techniques, which include Genetic Algorithm (DE,SCGA), Simulated Annealing (ASA, DSSA, SAHPS), Tabu & Direct Search (DTS, DIRECT), Deterministic (MCS, SNOBIT), and Trust-Region algorithm. The test functions for the experiments are Benchmark problems in Hedar & Fukushima (2004), which are evaluated with respect to efficiency and accuracy. Through the experiment, we analyse the computational complexity of the methods and finally discuss the pros and cons of them.

• 전기전자학회논문지
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• 제23권4호
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• pp.1353-1359
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• 2019

It is presented in this paper that the static output feedback (SOF) pole-assignment problem of some linear time-invariant systems can be completely resolved by parametrization in real Grassmann space. For the real Grassmannian parametrization, the so-called Plucker matrix is utilized as a linear matrix formula formulated from the SOF variable's coefficients of a characteristic polynomial constrained in Grassmann space. It is found that the exact SOF pole assignability is determined by the linear independency of columns of Plucker sub-matrix and by full-rank of that sub-matrix. It is also presented that previous diverse pole-assignment methods and various computation algorithms of the real SOF gains for 2-input, 2-output, 4^th order systems are unified in a deterministic way within this real Grassmannian parametrization method.

• Journal of applied mathematics & informatics
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• 제26권5_6호
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• pp.889-900
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• 2008

The problem of scheduling n jobs on a single machine is considered when the machine is subject to stochastic breakdowns. The objective is to minimize the weighted squared deviation of job completion times from a common due date. Two versions of the problem are addressed. In the first one the common due date is a given constant, whereas in the second one the common due date is a decision variable. In each case, a general form of deterministic equivalent of the stochastic scheduling problem is obtained when the counting process N(t) related to the machine uptimes is a Poisson process. It is proved that an optimal schedule must be V-shaped in terms of weighted processing time when the agreeable weight condition is satisfied. Based on the V-shape property, two dynamic programming algorithms are proposed to solve both versions of the problem.

• 품질경영학회지
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• 제34권2호
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• pp.122-128
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• 2006

One feature of a computer simulation experiment, different from a physical experiment, is that the output is often deterministic. Moreover the codes are computationally very expensive to run. This paper deals with the design and analysis of computer experiments(DACE) which is a relatively new statistical research area. We model the response of computer experiments as the realization of a stochastic process. This approach is basically the same as using a spatial linear model. Applications to the optimal mechanical designing and model calibration problems are illustrated. Algorithms for selecting the best spatial linear model are also proposed.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.176-181
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• 1992

In this paper, an adaptive generalized predictive control(GPC) algorithm which minimizes a N-stage cost function is proposed. The resulting controller is based on GPC algorithm and can be used in unknown plant parameters as the parameters of one step ahead predictor are estimated by recursive least squares method. The estimated parameters are extended to G,P, and F amtrix which contain the parameters of N step ahead predictors. And the minimization of cost function assuming no constraints on future controls results in the projected control increment vector. Hence this adaptive GPC algorithm can be used for either unknown system or varing system parameters, and it is also shown through simulations that the algorithm is robust to the variation of system parameters. This adaptive GPC scheme is shown to have the same stability properties as the deterministic GPC, and requires small amount of calculation compared to other adaptive algorithms which minimize N-stage cost function. Especially, in case that the maximum output horizon is 1, the proposed algorithm can be applicable to direct adaptive GPC.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권5호
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• pp.976-998
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• 2011

This paper attempts to maximize the operator's revenue while simultaneously providing a multi-constraint, multi-hop and deterministic QoS provisioning for real time traffic in IEEE 802.16m based 4G networks. The optimal solution to such a problem is NP-complete and therefore not feasible to be solved in a tolerable polynomial time. For this reason, we also provide a simple price based greedy heuristic to be used along with the admission control. Simulation results for different QoS schemes show that the heuristic produces a revenue that is very close to the optimal revenue, and is far more aggressive than the size based and other common algorithms that are computationally feasible to be implemented in IEEE 802.16m.