• 대한교통학회지
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• 제14권4호
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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.

• 한국지하수토양환경학회:학술대회논문집
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• 한국지하수토양환경학회 2002년도 추계학술발표회
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• pp.24-27
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• 2002

The optimal designs of groundwater problems of contaminant containment and cleanup using linear programming and genetic algorithm are provided. In the containment problem, genetic algorithm shows the superior feature to linear programming. In cleanup problem, genetic algorithm makes reasonable optimal design. Un this study, it is demonstrated through numerical experiments that genetic algorithm can be applied to remedial designs of groundwater problems.

• 경영과학
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• 제19권1호
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• pp.67-75
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• 2002

This paper deals with the visualization method of solutions of the linear programming Problem. We used the revised simplex method for the LP algorithm. To represent the solutions at each iteration, we need the informations of feasible legion and animated effect of solutions. For the visualization in high dimension space, we used the method of Projection to the three dimensions if the decision variable vector is over three dimensions, and we studied the technique of preserving original Polyhedral information such as the number of vertices. In addtion, we studied the method of visualizing unbounded feasible region and the adjacency relationship of the vortices welch is Indispensable to cisualize feasible legion.

• Communications for Statistical Applications and Methods
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• 제8권3호
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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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• 제28권3_4호
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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.

• 한국산학기술학회논문지
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• 제7권4호
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• pp.690-696
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• 2006

본 연구는 연구논제[1]에서 제안한 보정방법을 평창강 지역 11개 강우관측소를 대상으로 적용하였다. 또한 본 연구는 방법별 오차범위 및 주변관측소 개수에 따른 공간적 분포 영향을 분석하였다. 연구 적용 결과 선형계획법이 가장 작은 오차를 나타내었으나 계산을 위한 프로그램이 필요하므로 현장의 실무적용에는 어려움이 있는 것으로 나타났다. 역거리법은 선형계획법과 비교해서 비교적 간단하고 정확한 결과를 보이는 것으로 나타났다. 따라서, 본 연구결과는 강우량 보정의 정확도를 높이는데 기여할 수 있을 것으로 판단된다.

• 한국인터넷방송통신학회논문지
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• 제23권3호
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• pp.139-143
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• 2023

제품 포트폴리오 문제(PPP)는 n개 제품 들 중에서 최대 이익을 창출하도록 특정 제품의 생산량을 결정하는 최적화 문제이다. 이러한 최적화 문제를 풀 수 있는 유일한 방법으로 선형계획법(LP)이 알려져 있다. 선형계획법은 n개의 선형함수를 최적화시키는 문제로 LINGO나 엑셀 해결사 등을 활용하는 실정이다. 본 논문은 제품 원가 대비 이익 비율인 CPR 개념을 도입하여 CPR 내림차순으로 정렬한 후, 최대 CPR 제품부터 허용된 최대 생산량을 실제 생산량으로 수기 식으로 결정하는 단순한 알고리즘을 제안하였다. 6개의 실험 데이터에 제안된 알고리즘을 적용한 결과 선형계획법에 비해 보다 정확한 결과를 얻을 수 있음을 보였다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.408-410
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• 2003

In this paper, an improved gradient direction assisted linking algorithm is proposed. This algorithm begins with initial seeds satisfying some local criteria. Then it will search along the direction provided by the initial point. A window will be generated in the gradient direction of the current point. Instead of the conventional method which only considers the value of the local salient structure, an improved mathematical model is proposed to describe the desired linear features. This model not only considers the value of the salient structure but also the direction of it. Furthermore, the linking problem under this model can be efficiently solved by dynamic programming method. This algorithm is tested for linear features detection in IKONOS images. The result demonstrates this algorithm is quite promising.

• 한국경영과학회지
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• 제7권1호
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• pp.45-50
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• 1982

The present paper provides a method for solving a complementary programming problem with quadratic objective function subject to linear constraints. The procedure developed is based on the simplex method for quadratic programming problem. An example is added to illustrate the procedure.

• Journal of applied mathematics & informatics
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• 제15권1_2호
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• pp.333-341
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• 2004

In the real world there are many linear programming problems where all decision parameters are fuzzy numbers. Several approaches exist which use different ranking functions for solving these problems. Unfortunately when there exist alternative optimal solutions, usually with different fuzzy value of the objective function for these solutions, these methods can not specify a clear approach for choosing a solution. In this paper we propose a method to remove the above shortcoming in solving fuzzy number linear programming problems using the concept of expectation and variance as ranking functions