• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.53-56
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• 2000

The problem ( Ρ ) of optimizing a linear function d$\^$T/x over the set of efficient set for a multiple objective linear program ( Μ ) is difficult because the efficient set is nonconvex. There some interesting properties between the objective linear vector ｄ and the matrix of multiple objectives C and those properties lead us to establish criteria to solve ( Ρ ) with a linear program. In this paper we investigate a system of the linear equations C$\^$T/${\alpha}$=d and construct two linearly independent positive vectors ${\mu}$, ν such that ${\alpha}$=${\mu}$-ν. From those vectors ${\mu}$, ν, solving an weighted sum linear program for finding an efficient extreme point for the ( Μ ) is a way to get an optimal solution ( Ρ ). Therefore our theory gives an easy way of solving nonconvex program ( Ρ ) with a weighted sum linear program.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.3
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• pp.139-143
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• 2023

The product portfolio problem(PPP) is an optimization problem that determines the production quantity of a particular product to obtain the maximum profit among the n products. Linear programming(LP) is known as the only way to solve this optimization problem. The linear programming method is a problem that optimizes n linear functions and uses LINGO or Excel solver. This paper proposes a simple algorithm that uses CPR, a product cost-profit ratio, to sort in CPR descending order and then determines the maximum allowed production quantity by hand as the actual production quantity. As a result of applying the proposed algorithm to six experimental data, it was shown that more accurate results can be obtained compared to the linear programming method.

• Journal of the Korea Society of Computer and Information
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• v.15 no.9
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• pp.47-55
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• 2010

Linear constraint satisfaction optimization problem is a kind of combinatorial optimization problem involving linearly expressed objective function and complex constraints. Integer programming is known as a very effective technique for such problem but require very much time and memory until finding a suboptimal solution. In this paper, we propose a method to improve the search performance by integrating local search and integer programming. Basically, simple hill-climbing search, which is the simplest form of local search, is used to solve the given problem and integer programming is applied to generate a neighbor solution. In addition, constraint programming is used to generate an initial solution. Through the experimental results using N-Queens maximization problems, we confirmed that the proposed method can produce far better solutions than any other search methods.

• Journal of the Korea Society of Computer and Information
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• v.14 no.2
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• pp.27-35
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• 2009

Integer programming is a very effective technique for searching optimal solution of combinatorial optimization problems. However, its applicability is limited to linear models. In this paper, I propose an effective method for solving a nonlinear optimization problem by integrating the powerful search performance of integer programming and the flexibility of neighborhood search algorithms. In the first phase, integer programming is executed with subproblem which can be represented as a linear form from the given problem. In the second phase, a neighborhood search algorithm is executed with the whole problem by taking the result of the first phase as the initial solution. Through the experimental results using a nonlinear maximal covering problem, I confirmed that such a simple integration method can produce far better solutions than a neighborhood search algorithm alone. It is estimated that the success is primarily due to the powerful performance of integer programming.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.141-141
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• 2015

IPCC 5차 보고서에서 기술되어 있는 것처럼 기후시스템의 온난화는 명백하며, 1950년 이후 관측된 많은 변화들은 지난 수천 년간 전례가 없는 것이었다. 지구 온난화로 대표되는 기후변화는 이제 일부 국가에 국한되는 문제가 아니라 전 지구적인 문제가 되었다. RCP 시나리오에 따라 차이는 있으나 대한민국의 경우 연평균 강수 총량은 증가할 것이라 예상되는 반면 총 예상 강우 일수는 감소하여 집중호우의 발생빈도가 증가될 것이라 예상되고 있다. 이에 따라 수자원의 효율적 이용에 대한 필요성 또한 증가하고 있는 실정이다. 본 연구에서는 수자원의 효율적 이용을 위해 한강수계 9개 댐(화천, 춘천, 소양강, 의암, 청평, 충주, 괴산, 횡성, 팔당)을 대상으로 HEC-ResPRM과 선형계획법을 이용하여 발전량을 최적화 하였다. HEC-ResPRM은 미공병단 수문공학센터에서 개발한 저수지운영 최적화 모형으로 홍수 조절, 관개, 발전, 레크리에이션 등 다양한 요구조건을 만족시킬 수 있는 최적의 저수지 운영방안 도출이 가능하다. 본 연구에서는 HEC-ResPRM 모형과 선형계획법을 이용한 운형모형의 결과자료를 비교하였으며 이를 통해 HEC-ResPRM 모형의 특징과 활용 가능성을 확인하였다.

• Information Systems Review
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• v.5 no.2
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• pp.203-217
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• 2003

Constraint Programming and Optimization have developed in different fields to solve common problems in real world. In particular, constraint propagation and linear Programming are their own fundamental and complementary techniques with the potential for integration to benefit each other. This intersection has evoked the efforts to combine both for a solution method to combinatorial optimization problems. Attempts to combine them have mainly focused on incorporating either technique into the framework of the other with traditional models left intact. This paper argues that integrating both techniques into an old modeling fame loses advantages from another and the integration should be molded in a new framework to be able to exploit advantages from both. The paper propose a declarative modeling framework in which the structure of the constraints indicates how constraint programming and optimization solvers can interact to solve problems.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.5
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• pp.187-196
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• 2010

We present a link that allows Excel to call the functions in the lp_solve system. lp_solve is free software licensed under the GPL that solves linear and mixed integer linear programs of moderate size. Our link manages the interface between Excel and lp_solve. Excel has a built-in add-in named Solver that is capable of solving mixed integer programs, but only with fewer than 200 variables. This link allows Excel users to handle substantially larger problems at no extra cost. Futhermore, we introduce that a network drawing method in Excel using arc adjacency lists of a network.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.11
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• pp.787-794
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• 2019

In this paper, a Mixed Integer Linear Programming(MILP) approach for solving optimal Weapon-Target Assignment(WTA) problem of multiple dissimilar Closed-In Weapon Systems (CIWS) is proposed. Generally, WTA problems are formulated in nonlinear mixed integer optimization form, which often requires impractical exhaustive search to optimize. However, transforming the problem into a structured MILP problem enables global optimization with an acceptable computational load. The problem of interest considers defense against several threats approaching the asset from various directions, with different time of arrival. Moreover, we consider multiple dissimilar CIWSs defending the asset. We derive a MILP form of the given nonlinear WTA problem. The formulated MILP problem is implemented with a commercial optimizer, and the optimization result is proposed.

• Journal of Intelligence and Information Systems
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• v.10 no.2
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• pp.165-187
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• 2004

Constraint Programming in AS and Optimization in OR started and have grown in different backgrounds to solve common decision-making problems in real world. This paper tries to integrate results from those different fields by suggesting a hybrid solver as an integration framework. Starting with an integrating modeling language, a way to implement a hybrid solver will be discussed using Warren's abstract machine and an finite domain constraint programming solver structures. This paper will also propose some issues rising when implementing the hybrid solver and provide their solutions.

• Journal of Korean Society of Steel Construction
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• v.16 no.1 s.68
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• pp.123-134
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• 2004

In this research, a multilevel decomposition technique to enhance the efficiency of the configuration optimization of truss structures was proposed. On the first level, the nonlinear programming problem was formulated considering cross-sectional areas as design variables, weight, or volume as objective function and behavior under multiloading condition as design constraint. Said nonlinear programming problem was transformed into a sequential linear programming problem. which was effective in calculation through the approximation of member forces using behavior space approach. Such approach has proven to be efficient in sensitivity analysis and different form existing shape optimization studies. The modified method of feasible direction (MMFD) was used for the optimization process. On the second level, by treating only shape design variables, the optimum problem was transformed into and unconstrained optimal design problem. A unidirectional search technique was used. As numerical examples, some truss structures were applied to illustrate the applicability. and validity of the formulated algorithm.