• Journal of Korean Institute of Industrial Engineers
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• v.31 no.3
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• pp.248-256
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• 2005

In this paper, we compare two EOQ based inventory models under total cost minimization and profit maximization to investigate the difference in the optimal solutions. First of all, optimal solutions for both models through geometric programming (GP) techniques are found considering production (lot sizing) as well as marketing (pricing) decisions. An investigation of the effects of the changes in the optimal solutions according to varied parameters is performed by studying optimality conditions as well as by performing numerical analysis. We then conduct comparative analysis between the models to show the relationships between the optimal solutions of the models where certain conditions in the cost per unit and the demand per unit time are given. Several interesting economic implications and managerial insights are observed from this analysis.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.406-412
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• 1996

Optimal trajectory for a robot manipulator minimizing actuator torques or energy consumption in a fixed traveling time is obtained in the presence of obstacles. All joint displacements are represented in finite terms of Fourier cosine series and the coefficients of the series are obtained optimally by nonlinear programming. Thus, the geometric path need not be prespecified and the full dynamic model is employed. To avoid the obstacles, the concept of penalty area is newly introduced and this penalty area is included in the performance index with an appropriate weighting coefficient. This optimal trajectory will be useful as a geometric path in the minimum-time trajectory planning problem.

• Journal of Agricultural Extension & Community Development
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• v.23 no.2
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• pp.123-133
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• 2016

According to increasing the number of rice farm households, it is important to find optimal farm scale, farm crops, and labour constraints depending on growth time. The study aims to analyze the optimal farming system using the linear programming in Seosan county, Chungnam. The survey was conducted in-depth interview to collect data from one farm household. Results show that farmers change their some crops in dry filed into ginger and hire farm labours in April. The findings should be of interest to rice farmers and policy makers to manage their farm effectively and to support them.

• Journal of Korea Water Resources Association
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• v.35 no.4 s.129
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• pp.367-374
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• 2002

Water supply plan by optimal conjunctive use of surface and ground water is studied to prepare expected water deficit in near future. The optimization model for conjunctive use of surface and ground water is developed using discrete differential dynamic programming technique to maximize net benefit by water supply. As a result of applying the model to Namdaechun river located in Yangyang, it is found that water supply reliability using optimal conjunctive use of surface and ground water is much higher than reliability using surface water alone.

• Proceedings of the KIEE Conference
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• 2003.11a
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• pp.233-235
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• 2003

This paper describes a new methodology to get pareto-optimal generation planning for decision-making. To get optimal generation planning consider total quantity of contamination for the specified term, authors employ dynamic programming. And, in the course of dynamic programming, pareto optimal solution can be obtained. So, a most proper solution can be selected by derision-maker. The usefulness is verified by applying It to the test system.

• Journal of Korea Water Resources Association
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• v.38 no.12 s.161
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• pp.1021-1028
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• 2005

This study purpose to develop simulation model of optimal design condition of urban storm sewer system considering risk. Urban Storm Sewer Optimal Design Model(USSOD) can compute pipe capacity, pipe slope, crown elevation, excavation depth, risk and return cost in the condition of design discharge. Rational formula is adopted for design discharge and Manning's formula is used for pipe capacity. Discrete differential dynamic programming(DDDP) technique which is a kind of dynamic programming(DP) is used for optimization and first order second moment approximation method and uncertainty analysis is also for developing model. USSOD is applied to hypothetical drainage basin to test and verify, which resulted economical and efficient design in urban drainage sewer system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.1C
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• pp.90-97
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• 2009

The advantages of the orthogonal frequency division multiplexing (OFDM) are high spectral efficiency, resiliency to RF interference, and lower multi-path distortion. To further utilize vast channel capacity of the multiuser OFDM, one has to find the efficient adaptive subchannel and bit allocation among users. In this paper, we propose an 0-1 integer programming model formulating the optimal subchannel and bit allocation problem of the multiuser OFDM. We employ a dual-decomposition method that provides a tight linear programming (LP) relaxation bound. Simulation results are provided to show the effectiveness of the 0-1 integer programming model. MATLAB simulation on a system employing M-ary quardarature amplitude modulation (MQAM) assuming a frequency-selective channel consisting of three independent Rayleigh multi-paths are carried with the optimal subchannel and bit allocation solution generated by 0-1 integer programming model.

• Journal of the Korea Society of Computer and Information
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• v.14 no.4
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• pp.1-8
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• 2009

In this paper, we deal an implementation of the software that produces sub-optimal solution of cutting-ironbar planning problem using dynamic programming. Generally, it is required to design an optimization algorithm to accept the practical requirements of cutting ironbar manufacturing. But, this problem is a multiple-sized 1-dimensional cutting stock problem and Linear Programming approaches to get the optimal solution is difficult to be applied due to the problem of explosive computation and memory limitation. In order to overcome this problem, we reform the problem for applying Dynamic Programming and propose a cutting-ironbar planning algorithm searching the sub-optimal solution in the space of fixed amount of combinated columns by using heuristics. Then, we design a graphic user interfaces and screen displays to be operated conveniently in the industry workplace and implement the software using open-source GUI library toolkit, GTK+.

• Journal of the military operations research society of Korea
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• v.32 no.2
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• pp.21-39
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• 2006

This paper presents a mixed linear and integer goal programming (GP) model to aid in strategic planning and scheduling of guard soldiers. The proposed model is a general-purpose model, hence can be used to produce an optimal schedule with respect to any user-provided combination of guard post objectives and soldier preferences. We extensively test the usefulness of the model on a real-life dataset from a guard post in the ROK Army with using three objectives set by the guard post and three preferences provided by individual solders. Numerical results and analysis from these experiments show that the proposed guard scheduling model efficiently as well as effectively generates an optimal guard schedule and can also be used for an optimal revision of any existing schedule. In summary, these illustrate that the proposed model can be practically used for optimal planning and scheduling of guard soldiers in guard posts.

• Journal of the Earthquake Engineering Society of Korea
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• v.7 no.5
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• pp.93-102
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• 2003

An optimal design method for hybrid structural control system of building structures subject to earthquake excitation is presented in this paper. Designing a hybrid structural control system may be defined as a process that optimizes the capacities and configuration of passive and active control systems as well as structural members. The optimal design proceeds by formulating the optimization problem via a multi-stage goal programming technique and, then, by finding reasonable solution to the optimization problem by means of a goal-updating genetic algorithm. In the multi-stage goal programming, design targets(or goals) are at first selected too correspond too several stages and the objective function is th n defined as the sum of the normalized distances between these design goals and each of the physical values, that is, the inter-story drifts and the capacities of the control system. Finally, the goal-updating genetic algorithm searches for optimal solutions satisfying each stage of design goals and, if a solution exists, the levels of design goals are consecutively updated to approach the global optimal solution closest too the higher level of desired goals. The process of the integrated optimization design is illustrated by a numerical simulation of a nine-story building structure subject to earthquake excitation. The effectiveness of the proposed method is demonstrated by comparing the optimally designed results with those of a hybrid structural control system where structural members, passive and active control systems are uniformly distributed.