• 전산구조공학
• /
• 제5권1호
• /
• pp.133-142
• /
• 1992

본 논문은 수식화의 특이성 때문에 구조 최적화 문제에 거의 사용되지 않고 있는 선형 goal programming을 대규모 비선형 구조 최적화에 응용하는 방법을 제시한다. 이 방법은 다기준 최적화의 도구로 사용되는데 그 까닭은 goal programming이 목적함수와 제한조건등을 정의하는데 있어서 발생하는 난점들을 제거해 주기 때문이다. 이 방법은 비선형 goal 최적화 문제들의 해를 얻기 위해서 유한요소해석, 선형 goal programming기법, 그리고 계속적인 선형화 기법을 이용한다. 즉, 대규모 비선형 구조 최적화 문제를 비선형 goal programming형태로 전환시키는 일반적인 수식화 방법을 제시하고, 얻어진 비선형 goal 최적화 문제를 풀기 위한 계속적인 선형화 방법에 대해서도 논의한다. 설계도구로서 이 방법의 유효성을 논증하기 위하여 10, 25 및 200트러스의 사례를 가지고 응력제한조건들의 최소무게 구조 최적화 문제에 대한 해를 모색하며 이를 다른 연구결과와 비교검토한다.

• 한국경영과학회지
• /
• 제10권1호
• /
• pp.14-30
• /
• 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.

• Journal of applied mathematics & informatics
• /
• 제24권1_2호
• /
• pp.449-460
• /
• 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.

• 조명전기설비학회논문지
• /
• 제18권1호
• /
• pp.146-153
• /
• 2004

본 연구에서는 Fuzzy Goal Programming을 이용하여 배전계통에서 분산형 전원의 설치 및 운영에 대한 새로운 방안을 제시하였다. 분산형전원의 설치 및 운영을 위하여 최적화 알고리즘의 탐색공간의 크기를 줄이면서 계통상황 변동에 적합하게 정식화하였다. 특히, 목적함수인 계통 유효전력손실과 제약조건인 분산형전원의 수 또는 총용량 및 모선전압에 대하여 각각의 부정확한 성질을 평가하기 위하여 퍼지 Goal Programing으로 모델링 하였으며, 유전알고리즘을 사용하여 최적해를 탐색하였다.

• 한국경영과학회지
• /
• 제6권1호
• /
• pp.15-23
• /
• 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 Data and Information Science Society
• /
• 제17권2호
• /
• pp.599-607
• /
• 2006

We propose a simple new analytic method for solving a fuzzy goal programming (FGP) problem with general membership functions of fuzzy goals and re-examine a previously defined method for dealing with fuzzy weights for each of the goals. Several illustrative examples are given.

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

• Journal of the Korean Data and Information Science Society
• /
• 제15권2호
• /
• pp.457-465
• /
• 2004

Ramik[7] introduced a fuzzy goal programming (FGP)problem that generalizes a standard goal programming (GP) problem with fuzzy alternatives, fuzzy objective functions and fuzzy deviation functions for measuring the deviation between attained and desired goals being fuzzy. However, it is known that this FGP tends to produce an approximate solution since it uses an approximate fuzzy multiplication operation to solve the resultant fuzzy model. In this paper, we show that this FGP sometimes leads to the wrong decision. We also propose a procedure that gets the exact solution to overcome these problems. The method is based on $T_M$ (min norm)-based fuzzy operations using $\alpha-cut$ representations. We consider the same example as used in Ramik and investigate how our procedures are compared to Ramik's.

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

• Industrial Engineering and Management Systems
• /
• 제13권4호
• /
• pp.369-382
• /
• 2014

This paper introduces a new multi-product multi-period multi-objective aggregate production planning problem. The proposed problem is modeled using multi-objective mixed-integer mathematical programming. Three objective functions, including minimizing total cost, maximizing customer services level, and maximizing the quality of end-product, are considered, simultaneously. Several constraints such as quantity of production, available time, work force levels, inventory levels, backordering levels, machine capacity, warehouse space and available budget are also considered. Some parameters of the proposed model are assumed to be qualitative and modeled using fuzzy sets. Then, a fuzzy goal programming approach is proposed to solve the model. The proposed approach is applied on a real-world industrial case study of a color and resin production company called Teiph-Saipa. The approach is coded using LINGO software. The efficacy and applicability of the proposed approach are illustrated in the case study. The results of proposed approach are compared with those of the existing experimental methods used in the company. The relative dominance of the proposed approach is revealed in comparison with the experimental method. Finally, a data dictionary, including the way of gathering data for running the model, is proposed in order to facilitate the re-implementation of the model for future development and case studies.