• Magazine of the Korean Society of Agricultural Engineers
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• v.36 no.2
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• pp.111-122
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• 1994

In this study, an algorithm which can be applied to the optimum design of simple steel plate girders was developed, and efficient optimization strategies for the solution of algorithm were found out. The optimum design algorithm consists of 3-levels of optimization. In the first and second levels of optimization, the absolute maximum bending moment and shearing force are extracted and in the third level of optimization, the optimum cross section of steel plate girder is determined. For the optimum design of cross section, the objective function is formulated as the total area of cross section and constraints are derived in consideration of the various stresses and the minimum dimension of flange and web based on the part of steel bridge in the Korea standard code of road bridge. Sequential unconstrained minimization technique using the exterior penalty function method(SUMT-EP), sequential linear programming(SLP) and sequential quadratic programming (SQP) are proved to be efficient and robust strategies for the optimum design of simple plate girder cross section. From the reliable point of view, SLP is the most efficient and robust strategy and SQP is the most efficient one from the viewpoint of converguency and computing time.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.4
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• pp.177-182
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• 2021

Generally, the linear programming (LP) with O(n⁴) time complexity is applied to mixture optimization problem that can be produce the given ingredients grade product with minimum cost from mixture of various raw materials. This paper suggests heuristic algorithm with O(n log n) time complexity to obtain the solution of this problem. The proposed algorithm meets the content range of the components required by the alloy steel plate while obtaining the minimum raw material cost, decides the quantity of raw material that is satisfied with ingredients grade for ascending order of unit cost. Although the proposed algorithm applies simple decision technique with O(n log n) time complexity, it can be obtains same solution as or more than optimization technique of linear programing.

• Journal of Korean Institute of Industrial Engineers
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• v.6 no.2
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• pp.21-29
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• 1980

This paper deals with the capital budgeting problem of a firm where investments are risky and interrelated. The established models might be classified into two categories; One is the chance-constrained programming model and the other is the expected utility maximization model. The former has a rather limited objective function and does not consider the risk in direct manner. The latter, on the other hand, might lead to a wrong decision because it uses an approximate value of expected utility. This paper attempts to extend the applicability of the chance-constrained programming model by modifying its objective function into a more general form. The capital budgeting problem is formulated as a nonlinear 0-1 integer programming problem first, and is formulated into a linear 0-1 integer programming problem for finding a lower-bound solution of the original problem. The optimal solution of the original problem is then obtained by branch & bound algorithm.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.2
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• pp.195-205
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• 2002

Crew scheduling is the problem of pairing crews with each of the vehicles in operation during a certain period of time. A typical procedure of crew schedule optimization consists of enumerating all possible pairings and then selecting the subset which can cover all the operating vehicles, with the goal of minimizing the number of pairings in the subset. The linear programming approach popularly adopted for optimal selection of pairings, however, is not applicable when the objective function cannot be expressed in a linear form. This paper proposes a method of integrating integer programming and heuristic search to solve difficult crew scheduling problems in which the objective function cannot be expressed in linear form and at the same time the number of crews available is limited. The role of heuristic search is to improve the incomplete solution generated by integer programming through iterative repair. Experimental results show that our method outperforms human experts in terms of both solution quality and execution time when applied to real world crew scheduling Problems which can hardly be solved by traditional methods.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.151-157
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• 2003

OLS로 알려진 기존의 주절 방법은 변수수의 증가에 따라 다중공선성(Multicollinearity)의 문제와 더불어 해석력(Interpretability)이 떨어지는 문제를 가지게 된다. 본 연구에서는 파라미터의 절대값의 크기(L1-Norm)에 제약을 줌으로써 이와 같은 OLS의 문제를 해결할 수 있는 동시에, 잔차의 제곱합대신 절대오차를 사용하는 Least Absolute Value(LAV) 방법을 사용함으로써 이상치에 로버스트한 결과를 주는 방법론을 제안한다. 또한. 본 연구에서 제안하는 방법이 선형계획법에 의해 모델처럼 될 수 있는 특성으로 인해 제약조건이 있는 이차 형태의 최적화 문제보다 수행 속도면에서 뛰어난 결과를 주는 것을 수치예제을 통해 보인다.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.7
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• pp.716-726
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• 2010

In this research, design optimization of an aircraft wing has been performed using the fully automated Multidisciplinary Design Optimization (MDO) framework, which integrates aerodynamic and structural analysis considering nonlinear structural behavior. A computational fluid dynamics (CFD) mesh is generated automatically from parametric modeling using CATIA and Gambit, followed by an automatic flow analysis using FLUENT. A computational structure mechanics (CSM) mesh is generated automatically by the parametric method of the CATIA and visual basic script of NASTRAN-FX. The structure is analyzed by ABAQUS. Interaction between CFD and CSM is performed by a fully automated system. The Response Surface Method (RSM) is applied for optimization, helping to achieve the global optimum. The optimization design result demonstrates successful application of the fully automated MDO framework.

• Journal of Korean Society of Forest Science
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• v.85 no.2
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• pp.172-179
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• 1996

This paper described the application of fuzzy multiobjective linear programming to solving a multiple-use problem of forest resources management. At first the concepts of linear programming, fuzzy linear programming and fuzzy multiobjective linear programming were introduced briefly. In order to illustrate a role of fuzzy multiobjective linear programming in the process of multiple-use forest planning, the natural recreation forest in Mt. Yoomyung was selected for this study. A fuzzy multiobjective linear programming model is formulated with data obtained from this Mt. Yoomyumg natural recreation forest to solve the multiple-use management planning problem of forest resources. Finally, the results, which were obtained from the calculation of this model, were discussed. The maximal value of the membership function(${\lambda}$) was 0.29, when the timber production and the forest recreation function were optimized at the same time through the fuzzy multiobjective linear programming. The cutting area in each period was 102.7ha, while total cutting area was 410.8ha for 4 periods. During 4 periods $57,904m^3$ will be harvested from this natural recreation forest and at the same time total visitors were estimated to be about 8.6 millions persons.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.5
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• pp.46-55
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• 2006

In general, 3-dimensional point-mass equation has been widely used for the trajectory optimization of the fixed-wing aircraft and reentry vehicle. But it should be modified and represent target vehicle's own characteristics. For a lighter-than-air vehicle such as an airship, there exists different and peculiar flight characteristics compared with the aircraft. The first part of this paper is to derive the dynamic equation of motion for the mid-altitude unmanned airship and the second part is to obtain the optimal trajectories under the minimal time flight given constraints. The trajectory optimization problem is converted into the nonlinear programming problem using Sequential Quadratic Programming approach. Finally numerical solutions are presented in the last part of the paper.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.4 no.3
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• pp.27-42
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• 1984

The complexity and expensiveness of water resources projects have made optimum operation and design by computer-based techniques of increasing interest in recent years. Water resources problems in real world need many decisions under numerous constraints. In addition there are nonlinearities in the state and return function. This mathematical and technical troublesome must be overcome so that the optimum operation polices are determined. Then traditional dynamic optimization method encountered two major-cruxes: variable discretization and appearance of constraints. Even several recent methods which based on the Differential Dynamic Programming(DDP) have some difficulties in handling of constraints. This paper has presented New DDP which is applicable to multi-reservoir control. It is intended that the method suggested here is superior to abailable alternatives. This belief is supported by analysis and experiments(New DDT does not suffer course of dimensionality and requires no discretization and is able to handle easily all constraints nonlinearity).

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.1
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• pp.151-156
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• 2023

This paper deals with the optimization problem that decides the number of advertising for any media among various medium to maximize the perception quality index of new product meets the given budget and over the minimum reached people constraints. For this problem, there is only in used the mathematical approach as linear programming (LP) software package and has been unknown the polynomial time algorithm. In this paper we suggest the heuristic algorithm with O(nlog n)time complexity to solve the optimal solution for this problem. This paper suggests the evaluation index to select the media most economically-efficient way and decides the media and the number of advertisement. While we utilize Excel, the proposed algorithm can be get the same optimal solution as LP for experimental data.