• Magazine of the Korean Society of Agricultural Engineers
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• v.39 no.2
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• pp.74-85
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• 1997

This study aims at the development of a mathematical approach for the optimal water allocation in the river basin where available water is not in sufficient. Its optimal allocation model is determined from the comparison and analysis of mathematical programming techniques such as transportation programming and dynamic programming models at its optimal allocation models. The water allocation system used in this study is designed to be the optimal water allocation which can satisfy the water deficit in each district through inter-basin water transfer between Kumho river basin which is a tributary catchment of Nakdong river basin, and the adjacent Hyungsan river basin, Milyang river basin and Nakdong upstream river basin. A general rule of water allocation is obtained for each district in the basins as the result of analysis of the optimal water allocation in the water allocation system. Also a comparison of the developed models proves that there is no big difference between the models Therefore transportation programming model indicates most adequate to the complex water allocation system in terms of its characteristics It can be seen, however, that dynamic programming model shows water allocation effect which produces greater net benefit more or less.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.146.4-146
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• 2001

Various methods have been proposed for the time series prediction. Most of the conventional methods only optimize parameters of mathematical models, but to construct an appropriate functional form of the model is more difficult in the first place. We employ the Genetic Programming (GP) to construct the functional form of prediction models. Our method is distinguished because the model parameters are optimized by using Back-Propagation (BP)-like method and the prediction model includes discontinuous functions, such as if and max, as node functions for describing complicated phenomena. The above-mentioned functions are non-differentiable, but the BP method requires derivative. To solve this problem, we develop ...

• Korean Management Science Review
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• v.30 no.3
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• pp.99-111
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• 2013

This paper studies the scheduling problem of storing and retrieving assembly blocks in a temporary storage yard. The objective is to minimize the number of relocations of blocks while the constraints for storage and retrieval time windows are satisfied. We present an integer programming model based on multi-commodity network flows, and the three revised models based on the properties of the problem. We show that the revised models are more efficient than the generic model through the numerical experiments.

• Journal of the Korean Mathematical Society
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• v.50 no.4
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• pp.727-753
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• 2013

In this paper, we introduce three new broad classes of second-order generalized convex functions, namely, ($\mathcal{F}$, $b$, ${\phi}$, ${\rho}$, ${\theta}$)-sounivex functions, ($\mathcal{F}$, $b$, ${\phi}$, ${\rho}$, ${\theta}$)-pseudosounivex functions, and ($\mathcal{F}$, $b$, ${\phi}$, ${\rho}$, ${\theta}$)-quasisounivex functions; formulate eight general second-order duality models; and prove appropriate duality theorems under various generalized ($\mathcal{F}$, $b$, ${\phi}$, ${\rho}$, ${\theta}$)-sounivexity assumptions for a multiobjective programming problem containing arbitrary norms.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.1
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• pp.39-54
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• 1997

This paper presents four process models for machining processes : 1) an economical mathematical model of machining process, 2) a prediction model for surface roughness, 3) a decision model for fuzzy cutting conditions, and 4) a judgment model of machinability with automatic selection of cutting conditions. Each model was developed the economic machining, and these models were applied to theories widely studied in industrial engineering which are nonlinear programming, computer simulation, fuzzy theory, and neural networks. The results of this paper emphasize the human oriented domain of a nonlinear programming problem. From a viewpoint of the decision maker, fuzzy nonlinear programming modeling seems to be apparently more flexible, more acceptable, and more reliable for uncertain, ill-defined, and vague problem situations.

• The Journal of the Korea Contents Association
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• v.13 no.12
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• pp.680-689
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• 2013

In recent, much attention has been paid to the educational serious games that provide both fun and learning effects. However, most educational games have been targeted at the infants and children, and it is still hard to use such games in higher education. On the contrary, this paper aims to develop an educational game for teaching mathematical programming to the undergraduates. It is well known that most puzzle games can be transformed into associated optimization problem and vice versa, and this paper proposes a simple educational game based on the subset sum problem. This game enables the users to play the puzzle and construct their own mathematical programming model for solving it. Moreover, the users are provided with appropriate instructions for modeling and their models are evaluated by using the data automatically generated. It is expected that the educational game in this paper will be helpful for teaching basic programming models to the students in industrial engineering or management science.

• IE interfaces
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• v.21 no.1
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• pp.1-7
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• 2008

In this paper we study the Minimum Edge Addition Problem(MEAP) to decrease the diameter of a graph. MEAP can be used for improving the serviceability of telecommunication networks with a minimum investment. MEAP is an NP-hard optimization problem. We present two mathematical programming models : One is a multi-commodity flow formulation and the other is a path partition formulation. We propose a branch-and-price algorithm to solve the path partition formulation to the optimality. We develop a polynomial time column generation sub-routine conserving the mathematical structure of a sub problem for the path partition formulation. Computational experiments show that the path partition formulation is better than the multi-commodity flow formulation. The branch-and-price algorithm can find the optimal solutions for the immediate size graphs within reasonable time.

• Journal of the Ergonomics Society of Korea
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• v.19 no.1
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• pp.11-22
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• 2000

In this research report, we are presenting several optimization models for cognitive systems by using stimulus-response matrix (S-R Matrix). Stimulus-response matrices are widely used for tabulating results from various experiments and cognition systems design in which the recognition and confusability of stimuli. This paper is relevant to analyze the optimization/mathematical programming models. The weakness and restrictions of the existing models are resolved by generalization considering average confusion of each subset of stimuli. Also, clustering strategies are used in the extended model to obtain centers of cluster in terms of minimal confusion as well as the character of each cluster.

• Journal of Environmental Science International
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• v.5 no.2
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• pp.229-241
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• 1996

This study was performed to find the most desirable emission reduction for each mobile source pollutant and the optimal control strategy at a given level of expenditures in Pusan City in 2000 by using the interactive s-constraint method developed by Chang-Hyo Lee and Hyung-Wook Kim, which isone of the mathematical programming models. The most desirable emission reduction is 7093 ton/year for particulate (TSP), 4871 ton/year for NOx, 5148 ton/year for HC and 36779 ton/year for CO. The optimal control strategy is as follows; 1. As to passenger car and taxi, limiting VKT (vehicle kilometers travelled) in congested areas will be necessary. In addition to this, improving vehicie inspection Program should be enforced. 2. As to small-gasoline bus, traffic adaptive control system will be necessary. 3. As to small-diesel bus, non-adjustable engine parameters will have to be applied. .4. As to heal bus and heart truck, catalytic trap oxidizer and limiting VKT in congested areas will do necessary. 5. As to motorcycle, 2-cycle motorcycles should be converted to 4-cycle motorcycles.

• Nuclear Engineering and Technology
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• v.49 no.1
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• pp.134-140
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• 2017

A well-performed core power control to track load changes is crucial in pressurized water reactor (PWR) nuclear power stations. It is challenging to keep the core power stable at the desired value within acceptable error bands for the safety demands of the PWR due to the sensitivity of nuclear reactors. In this paper, a state-space model predictive control (MPC) method was applied to the control of the core power. The model for core power control was based on mathematical models of the reactor core, the MPC model, and quadratic programming (QP). The mathematical models of the reactor core were based on neutron dynamic models, thermal hydraulic models, and reactivity models. The MPC model was presented in state-space model form, and QP was introduced for optimization solution under system constraints. Simulations of the proposed state-space MPC control system in PWR were designed for control performance analysis, and the simulation results manifest the effectiveness and the good performance of the proposed control method for core power control.