• 한국경영과학회지
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• 제11권2호
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• pp.79-87
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• 1986

This paper illustrates a new method to solve the fuzzy goal programming (FGP) problem. It is proved that the FGP proposed by Narasimhan can be solved on the basis of linear programming(LP) model. Narasimhan formulated the FGP problem as a set of $S^{K}$LP problems, each containing 3K constraints, where K is the number of fuzzy goals/constraints. Whereas Hanna formulated the FGP problem as a single LP problem with only 2K constraints and 2K + 1 additional variables. This paper presents that the FGP problem can be transformed with easy into a single LP model with 2K constraints and only one additional variables. And we propose extended FGP :(1) FGP with weights associated with individual goals, (2) FGP with preemptive prioities. The extended FGP has a framework that is identical to that of conventional goal programming (GP), such that the extended FGP can be applied with fuzzy concept to the all areas where GP can be applied.d.

• 한국지진공학회:학술대회논문집
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• 한국지진공학회 2003년도 추계 학술발표회논문집
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• pp.497-504
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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 nay 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. 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.

• 한국경영과학회지
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• 제11권1호
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• pp.36-43
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• 1986

In this study, the fuzzy programming is extended to handle various types of membership functions by transformation of the complicated fuzzy programming problems into the equivalent crisp linear programming problems with single objective. It is well-known that the fuzzy programming problem with linear membership functions (i.e., ramp type) can be easily transformed into a linear programming problem by introducing one dummy variable to minimize the worst unwanted deviation. However, until recently not many researches have been done to handle various general types of complicated linear membership functions which might be more realistic than ramp-or triangular-type functions. In order to handle these complicated membership functions, the goal dividing concept, which is based on the fuzzy set operation (i. e., intersection and union operations), has been prepared. The linear model obtained using the goal dividing concept is more efficient and single than the previous models [4, 8]. In addition, this result can be easily applied to any nonlinear membership functions by piecewise approximation since the membership function is continuous and monotone increasing or decreasing.

• 한국지진공학회논문집
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• 제7권5호
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• pp.93-102
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• 2003

이 연구에서는 지진하중을 받는 빌딩구조물에 대한 복합구조제어시스템의 최적설계방법을 제시한다. 복합구조제어시스템의 설계는 구조물의 부재뿐만 아니라 수동제어시스템 및 능동제어시스템의 용량 및 위치 최적화 과정으로 정의된다. 최적설계는 이 연구에서 제안된 다단계 목표계획법(Multi-Stage Goal Programming)을 이용하여 최적화문제를 정식화하고 목표갱신 유전자알고리즘(Goal-Updating Genetic Algorithm을 적용하여 합리적인 최적화를 진행해가는 과정으로 구성된다. 다단계 목표계획법에서는 구조물의 층간 상대변위와 제어시스템의 용량에 대한 설계목표를 여러 단계로 선정하고, 각 물리량과 설계목표간의 정규화된 거리 합으로서 목적함수를 정의한다. 목표갱신 유전자알고리즘은 각 단계별 설계목표를 만족하는 최적해를 검색하고, 현 단계의 모든 설계목표를 만족하는 최적해가 존재할 경우 설계목표를 순차적으로 갱신함으로써 보다 상위수준의 설계목표로 접근해 나아간다. 지진하중을 받는 9층의 빌딩구조물에 대한 수치 예를 통하여 복합구조제어시스템의 통합최적설계 과정을 기술하였고, 구조부재, 수동 및 능동제어시스템이 균등분포된 구조물과 최적 설계결과를 비교하여 제시하는 방법의 효율성을 검증하였다.

• Journal of Forest and Environmental Science
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• 제28권1호
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• pp.30-36
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• 2012

The total yield of Pinus koraiensis stands was reviewed along forest function by using goal programming, which is one of the operations research techniques. The 4 kinds of management goals are set to identify timber production in the Research Forest of Kangwon National University. As a result, scenario 1 was estimated the best timber production over 2,073 ha area and also 588 ha in the third quarter was showed the most timber harvest. The rate of timber harvest was separated by 10 to 50 percent in non-timber forest function in the scenario 1 and that model was applied to the Research Forest of Kangwon National University. The structure of the area and volume is showed to be balanced quarterly when rate of timber harvest at 10 to 20 percent.

• 경영과학
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• 제14권1호
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• pp.1-10
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• 1997

We consider a problem of estimating the economics of scale for the natural gas industries. The goal programming/constrained regression is employed for estimating the economics of scale for the natural gas industry, and the problem is formulated as a linear programing problem. Also the translog cost function is used to represent the cost structure for the natural gas industry. The Korean Gas Corporation was selected as a case study, and we demonstrate that the suggested goal programming/constrained regression approach is appropriate for estimating the economies of scale for the Korean nature gas industry.

• 한국경영과학회지
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• 제11권1호
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• pp.51-58
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• 1986

The propose of this study is to presnet a generalized linear/goal programming software, which has been developed to run on mickrocomputers with at least 512 K bytes of memory. The main characteristics of our algorithm for solving LP/GP problems are outlined as follows ; First, it uses the revised simplex algorithm, which is the most efficient computational procedure for computers. Second, it employs the sparse matrix technique to overcome the limited memory of microcomputers. Last, it uses the modified product form of invers (MPFI) to reduce round-off errors. The test runs with our code written in FORTRAN show that it can be used as an effective tool for solving linear/goal programming problems of considerable size.

• Journal of applied mathematics & informatics
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• 제13권1_2호
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• pp.323-334
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• 2003

This paper presents a goal-programming (GP) model for management decision-making for sugarcane fertilizer mix problems. Sensitivity analysis on the priority structure of the goals has been performed to obtain all possible solutions. The study uses Euclidean distance function to measure distances of all possible solutions from the ideal solution. The optimum solution is determined from the minimum distance between the ideal solution and other possible solutions of the problem. The optimum solution corresponds to the appropriate priority structure of the problem in the decision-making context. furthermore, the results obtained from sensitivity analysis on the cost of combination of fertilizers confirm the priority structure.

• 한국경영과학회지
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• 제19권1호
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• pp.113-122
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• 1994

This study proposes a new procedure to find an initial solution to reduce the number of iterations of goal programming. The process of computing an initial solution is divided into two steps in this study. Decision variables which satisfy feasibility using Gaussian eliminations construct an initial solution reducing the iterations in the first step. It uses LHS as a tool that decision variables construct an initial solution. The initial solution which is constructed by the first step computes the updated coefficient of the objective function in the second step. If the solution does not satisfy the optimality, the optimal solution using the Modified Simplex Method is sought. The developed method doesn't reduce the overall computing time of goal programming problems, because time is more required for the process of constructing an initial solution. But The result of this study shows that the proposed procedure can reduce the large number of iterations in the first step effectively.

• 한국경영과학회지
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• 제40권2호
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• pp.63-77
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• 2015

The territorial air that our sovereignty is being applied to is divided into several zones and areas. In order to use and manage them effectively, these zones and areas have laws, regulations and rules. The number of airspaces (MOA : Military Operation Area) and Ranges that are used in the military are limited and many airbases are being used for training. Currently the central department manages some, and the rest are independent airbases. Therefore, efficient allocation is not performed and the result occurs where airspaces and ranges are allocated unnecessarily. This is increasing the workload of staff leading to unnecessary re-work. To slove problem, this study proposed models for allocating airspaces and ranges using goal programming with multi-objective functions of minimizing the deviations of the target values.