• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.29 no.12
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• pp.638-644
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• 2017

Optimal cooling operation algorithm was developed based on a simulation case of a single family house model equipped with renewable energy facility. EnergyPlus simulation results were used as virtual test data. The model contained three energy storage elements: thermal heat capacity of the living room, chilled water storage tank, and battery. Their charging and discharging schedules were optimized so that daily electricity bill became minimal. As an optimization tool, linear programming was considered because it was possible to obtain results in real time. For its adoption, EnergyPlus-based house model had to be linearly approximated. Results of this study revealed that dynamic cooling load of the living room could be approximated by a linear RC model. Scheduling based on the linear programming was then compared to that by a nonlinear optimization algorithm which was made using GenOpt developed by a national lab in USA. They showed quite similar performances. Therefore, linear programming can be a practical solution to optimal operation scheduling if linear dynamic models are tuned to simulate their real equivalents with reasonable accuracy.

• Journal of the Korean Operations Research and Management Science Society
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• v.13 no.2
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• pp.205-205
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• 1988

This paper develops a simple interactive procedure which can be efficiently used to solve a bicriteria linear programming problem. The procedure exploits the relatively simple structure of the bicriterion linear programming problem. Its application to a transportation problem is also presented. The results demonstrate that the method developed in this paper could be easily applicable to any bicriteria linear program in general.

• Structural Engineering and Mechanics
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• v.26 no.1
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• pp.15-30
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• 2007

In the paper, one focuses on the problem of duality in non-linear programming, applied to the solution of no-tension problems by means of Limit Analysis (LA) theorems for Not Resisting Tension (NRT) models. In details, one demonstrates that, starting from the application of the duality theory to the non-linear program defined by the static theorem approach for a discrete NRT model, this procedure results in the definition of a dual problem that has a significant physical meaning: the formulation of the kinematic theorem.

• Journal of Korean Society of Transportation
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• v.14 no.4
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• pp.7-29
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• 1996

The optimal solution obtained by a linear programming model is to maximize the ramp inflow rate. It is argued in this paper that the maximization of inflow rate is different from the maximization of outflow rate under congested conditions. Therefore, this paper proposes a systematic searching procedure from a linear programing formulation to a integer programming : first obtain the optimal solution by a linear programming and then adding weight to linear programming then. solve the optimal solution again by integer programming i.e. The proposed method is an interactive approach. Measure of effectiveness by simulation models regards the real time data(O/D, queue, delay, etc), can be utilized in the proposed interactive process.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.11
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• pp.447-452
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• 2006

This paper presents a scheme to solve the congestion problem with phase-shifting transformer(PST) controls and power generation controls using linear programming method. A good design of PST and power generation control can improve total transfer capability(TTC) in interconnected systems. This paper deals with an application of optimization technique for TTC calculation. Linear programming method is used to maximize power flow of tie line subject to security constraints such as voltage magnitude and real power flow in interconnected systems. The results are compared with that of repeat power flow(RPF) and sequential quadratic programming(SQP). The proposed method is applied to 10 machines 39 buses model systems to show its effectiveness.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.6
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• pp.1059-1063
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• 2010

Shimming is an important technique in development of nuclear magnetic resonance (NMR) magnets where image resolution is highly dependent on magnetic field homogeneity. Classically, shimming may be categorized into two types: 1) active shimming that incorporates with extra coils and precise tuning of their currents; and 2)passive shimming that incorporates with pieces of steel placed in a bore of a main magnet and their uniform magnetization under homogeneous external fields. Additional magnetic fields, produced by the coils and/or the steel sheets, compensate original magnetic field from the main magnet in such a way that the total field becomes more homogeneous. In this paper, we developed a passive shimming method based on linear programming optimization. Linear programming is well known to be highly efficient to find a global minimum in various linear problems. We firstly confirmed the linearity of magnetization of ferromagnetic pieces under a presence of external magnetic fields. Then, we adopted the linear programming to find optimized allocation of the steel pieces in the inner bore of a main magnet to improve field homogeneity.

• The Journal of Fisheries Business Administration
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• v.3 no.1_2
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• pp.1-7
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• 1972

• Communications for Statistical Applications and Methods
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• v.8 no.3
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• pp.719-729
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• 2001

Overlap Maximization is a sampling technique to reduce survey costs and costs associated with the survey. It was first studied by Keyfitz(1951). Ernst(1998) presented a remarkable procedure for maximizing the overlap when the sampling units can be selected for two identical stratified designs simultaneously, But the approach involves mimicking the behaviour of nonlinear function by linear function and so it is less direct, even though the stratification problem for the overlap corresponds directly to the linear programming problem. furthermore, it uses the controlled selection algorithm that repeatedly needs zero-restricted controlled roundings, which are solutions of capacitated transportation problems. In this paper we suggest a comparatively simple procedure to use linear programming in order to maximize the overlap. We show how this procedure can be implemented practically.

• Journal of applied mathematics & informatics
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• v.9 no.2
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• pp.717-730
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• 2002

In this paper we use measure theory to solve a wide range of the nonlinear programming problems. First, we transform a nonlinear programming problem to a classical optimal control problem with no restriction on states and controls. The new problem is modified into one consisting of the minimization of a special linear functional over a set of Radon measures; then we obtain an optimal measure corresponding to functional problem which is then approximated by a finite combination of atomic measures and the problem converted approximately to a finite-dimensional linear programming. Then by the solution of the linear programming problem we obtain the approximate optimal control and then, by the solution of the latter problem we obtain an approximate solution for the original problem. Furthermore, we obtain the path from the initial point to the admissible solution.

• Journal of applied mathematics & informatics
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• v.28 no.3_4
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• pp.597-610
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• 2010

For a class of nonlinear bilevel programming problems in which the follower's problem is linear, the paper develops a genetic algorithm based on the optimality conditions of linear programming. At first, we denote an individual by selecting a base of the follower's linear programming, and use the optimality conditions given in the simplex method to denote the follower's solution functions. Then, the follower's problem and variables are replaced by these optimality conditions and the solution functions, which makes the original bilevel programming become a single-level one only including the leader's variables. At last, the single-level problem is solved by using some classical optimization techniques, and its objective value is regarded as the fitness of the individual. The numerical results illustrate that the proposed algorithm is efficient and stable.