• Journal of the Korean Society of Hazard Mitigation
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• v.11 no.2
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• pp.147-156
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• 2011

The purpose of multipurpose reservoir operation in flood season is to reduce the peak flood at a control point by utilizing flood control storage or to minimize flood damage by controlling release and release time. Therefore, the most important thing in reservoir operation for flood season is to determine the optimal release and release time. In this study, goal programming is used for the optimal reservoir operation in flood season. The goal programming minimizes a sum of deviation from the target value using linear programming or nonlinear programming to obtain the optimal alternative for the problem with more than two objectives. To analyze the applicability of goal programming, the historical storm data are utilized. The goal programming is applied to the reservoir system operation as well as single reservoir operation. Chungju reservoir is selected for single reservoir operation and Andong and Imha reservoirs are selected for reservoir system operation. The result of goal programming is compared with that of HEC-5. As a result, it was found that goal programming could maintain the reservoir level within flood control level at the end of a flood season and also maintain flood discharge within a design flood at a control point for each time step. The goal programming operation is different from the real operation in the sense that all inflows are assumed to be given in advance. However, flood at a control point can be reduced by calculating the optimal release and optimal release time using suitable constraints and flood forecasting system.

• Computational Structural Engineering
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• v.5 no.1
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• pp.133-142
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• 1992

This paper presents a method to apply the linear goal programming, which has rarely been used to the structural opimization problem due to its unique formulation, to large scale nonlinear structural optimization. The method can be used as a multicriteria optimization tool since goal programming removes the difficulty in defining an objective function and constraints. The method uses the finite element analysis, linear goal programming techniques and successive linearization to obtain the solution for the nonlinear goal optimization problems. The general formulation of the structural optimization problem into a nonlinear goal programming form is presented. The successive linearization method for the nonlinear goal optimization problem is discussed. To demonstrate the validity of the method, as a design tool, the minimum weight structural optimization problems with stress constraints are solved for the cases of 10, 25 and 200 trusses and compared with the results of the other works.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.67-71
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• 2010

홍수기 다목적댐 운영의 목적은 홍수조절용량을 최대한 이용하여 하류 주요 지점의 첨두홍수량을 저감시키거나, 계획홍수량을 초과하지 않도록 방류량과 방류시점을 조절함으로써 홍수 피해규모를 최소화하는 것이다. 본 연구에서는 홍수기 다목적댐 운영에서 다목적 최적화의 한 형태인 goal programming의 적용성을 검토하였다. 실제 강우사상을 이용하여 단일저수지 운영과 저수지 연계운영을 실시하였다. 단일 저수지 운영을 적용하기 위한 시험유역으로는 충주댐 유역을 선정하였고 저수지 연계운영을 적용하기 위한 시험유역으로는 안동댐과 임하댐 유역을 선정하였다. goal programming의 결과 분석을 위해 저수지 모의운영 모형인 HEC-5 모형의 결과와 비교, 분석하였다. goal programming을 이용할 경우 HEC-5 운영결과보다 안정적인 운영결과를 얻을 수 있었다. goal programming을 이용한 최적화 운영의 경우 전구간의 유입량을 알고 있다는 점에서 실제 저수지 운영과는 차이가 있다. 그러나 적절한 제약조건을 적용하고 홍수예경보를 이용하여 예보된 유입량을 활용하면 최적의 방류시점과 방류량을 산정하여 홍수기 다목적댐을 효율적으로 운영할 수 있으며 주요 지점의 홍수량도 저감할 수 있을 것으로 판단된다.

• Journal of Korean Society for Quality Management
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• v.20 no.1
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• pp.101-106
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• 1992

In this paper fuzzy goal programming problems with fuzzy constraints and fuzzy coefficients in both matrix and right hand side of the constraints set are considered. Because of fuzzy coefficients in both members of each constraint ranking methods for fuzzy numbers are considered. An additive model to solve fuzzy goal programming problems is formulated. The diversity of each methods provides a lot of different models of auxiliary linear programming problems from which fuzzy solutions to the fuzzy goal programming problem can be obtained.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.525-529
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• 1996

Decision environments involve a high degree of uncertainty as well as multiple, conflicting goals. Although traditional goal programming offers a means of considering multiple, conflicting goals and arrives at a satisficing solution in a deterministic manner, its major drawback is that decision makers often specify aspiration level of each goal as a single number. To overcome the problem of setting aspiration levels, chance constrained programming can be incorporated into goal programming formulation so that sampling information can be utilized to describe uncertainty distribution. Another drawback of goal programming is that it does not provide a systematic approach to set priorities and trade-offs among conflicting goals. To overcome this weekness, the analytic hierarchy process(AHP) is used in the model. Also, most goal programming models in the literature are of a linear form, although some nonlinear models have been presented. Consideration of risk in technological coefficients and right hand sides, however, leads to nonlinear goal programming models, which require a linear approximation to be solved. In this paper, chance constrained reformulation with linear approximation is presented for a 0-1 goal programming problem whose technological coefficients and right hand sides are stochastic. The model is presented with a numerical example for the purpose of demonstration.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.1
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• pp.146-153
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• 2004

This paper presents the method for the placement and operation of dispersed generator systems(DGs) using fuzzy goal programming in distribution systems. For the placement and operation of DGs the problem is formulated with reduction of search spaces and flexibility of system situations. Especially, the original objective function and constraints are transformed by fuzzy goal programming to evaluate their imprecise nature for the criterion of power loss minimization, the number or total capacity of DGs and the bus voltage deviation, and then solve the problem using genetic algorithm.

• Journal of the korean Society of Automotive Engineers
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• v.14 no.1
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• pp.64-73
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• 1992

본 논문은 비선형 goal programming을 이용하여 구조 최적화 문제들의 해를 얻는 방법을 제시한 다. 이 방법은 다기준 최적화의 도구로 사용되는데 그 까닭은 goal programming이 목적함수와 제한조건 등을 정의하는데 있어서 발생하는 난점들을 제거해 주며, 또한 설계목적의 우선 순위를 다루는 능력을 갖추고 있기 때문이다. 비선형 goal programming에 대한 구조 최적화의 모델이 제시된다. Hooke-Jeeves의 pattern 탐색, 수정된 Hooke-Jeeves의 Pattern 탐색, 그리고 Powell의 공액방향 탐색방향을 이용한 세 가지의 비선형 goal programming 들이 개발되고 토의된다. 설계 도구로서 이 방법의 유효성을 논증하기 위하여 사례의 해를 모색하며 이를 다른 연구결과와 비교 검토한다.

• Journal of applied mathematics & informatics
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• v.24 no.1_2
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• pp.449-460
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• 2007

Several fuzzy approaches can be considered for solving multi-objective transportation problem. This paper presents a fuzzy goal programming approach to determine an optimal compromise solution for the multiobjective transportation problem. We assume that each objective function has a fuzzy goal. Also we assign a special type of nonlinear (hyperbolic) membership function to each objective function to describe each fuzzy goal. The approach focuses on minimizing the negative deviation variables from 1 to obtain a compromise solution of the multiobjective transportation problem. We show that the proposed method and the fuzzy programming method are equivalent. In addition, the proposed approach can be applied to solve other multiobjective mathematical programming problems. A numerical example is given to illustrate the efficiency of the proposed approach.

• Journal of the Korean Operations Research and Management Science Society
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• v.6 no.1
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• pp.15-23
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• 1981

This paper deals with cross impact analysis for technology assessment. The focus of the paper is to develop new technique of cross impact matrix using goal programming method. In this study, the idea of cross impact analysis based on scenario generation method especially SMIC-74 (2) is expanded. Critical literature review on SMIC-74 is presented to discuss the mathematical rationale of consistent probability in cross impact analysis. A new model of cross impact analysis using goal programming to overcome the shortcomings of the scenario generation technique especially SMIC-74 is developed. This new technique is also applied to the assessment of the air pollution problems in Seoul Metropolitan area in Korea. The results of analysis give us following findings 1) Cross impact analysis using goal programming produce more meaningful solutions comparing to those of SMIC-74 2) Theoretical rationale of the objective function in the newly developed technique is more appropriate than that of SMIC-74.

• Journal of the Korean Operations Research and Management Science Society
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• v.10 no.1
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• pp.14-30
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• 1985

Recently, multiple criteria decision making has been well established as a practical approach to seek a satisfactory solution to a decision making problem. Goal programming is one of the most powerful MCDM tools with satisfying operational assumptions that reflect the actual decision making process in real-world situations. In this paper we propose an efficient method implemented on a microcomputer for solving linear goal programming problems. It is an iterative revised goal simplex method using the sparsity technique. We design as interactive software package for microcomputers based on this method. From some computational experiences, we can state that the revised iterative goal simplex method using the sparsity technique is the most efficient one for microcomputer for solving goal programming problems.