• 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.

• 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 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 Data and Information Science Society
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• v.15 no.2
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• pp.457-465
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• 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.

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.599-607
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• 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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.34
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• pp.185-191
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• 1995

In this research, a mathematical programming model is developed for the economic modeling of sampling plans based on two evaluation criteria : the outgoing quality and the average total inspection cost A fuzzy goal programming model and its solution procedure are proposed for the managers whose management objectives on the two evaluation criteria are not rigorous. To study the sensitivity of quality characteristic dependence on the resulting inspection plans, a numerical example is solved several times for a dependent model.

• Management Science and Financial Engineering
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• v.13 no.2
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• pp.1-27
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• 2007

This paper presents a fuzzy-goal programming(FGP) approach for Bi-Level Linear Multiple Objective Decision Making(BLL-MODM) problem in a large hierarchical decision making and planning organization. The proposed approach combines the attractive features of both fuzzy set theory and goal programming(GP) for MODM problem. The GP problem has been developed by fixing the weights and aspiration levels for generating pareto-optimal(satisfactory) solution at each level for BLL-MODM problem. The higher level decision maker(HLDM) provides the preferred values of decision vector under his control and bounds of his objective function to direct the lower level decision maker(LLDM) to search for his solution in the right direction. Illustrative numerical example is provided to demonstrate the proposed approach.

• Journal of the Korean Operations Research and Management Science Society
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• v.11 no.1
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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.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.512-516
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• 1998

Fuzzy mathematical programming (FMP) can be treated an uncertainty condition using fuzzy concept. Further, it can be extended to the multiple objective (or goal) programming problem, naturally. But we feel that FMP have some shortcomings such as the fuzzy number in FMP is the one dimesional possibility set, so it can not be represented the relationship between them, and, in spite of FMP includes some (uncertainty) fuzzy paramenters, many alogrithms are only obtained a crisp solution.In this study, we propose a method of FMS. Our method use the scenario approach (or fuzzy random variables) to represent the relationship between fuzzy numbers, and can obtain the fuzzy solution.

• Journal of the Korean Institute of Navigation
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• v.20 no.4
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• pp.59-70
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• 1996

A berth assignment problem has a direct impact on assessment of charges made to ships and goods. In this paper, we concerned with of fuzzy mathematical programming models for a berth assignment problem to achieved an efficient berth operation in a fuzzy environment. In this paper, we focus on the berth assignment programming with fuzzy parameters which are based on personal opinions or subjective judgement. From the above point of view, assume that a goal and a constraint are given by fuzzy sets, respectively, which are characterized by membership functions. Let a fuzzy decision be defined as the fuzzy set resulting from the intersection of a goal and constraint. This paper deals with fuzziness in all parameters which are expressed by fuzzy numbers. A fuzzy parameter defined by a fuzzy number means a possibility distribution of the parameters. These fuzzy 0-1 integer programming problems are formulated by fuzzy functions whose concept is also called the extension principle. We deal with a berth assignment problem with triangular fuzzy coefficients and propose a branch and bound algorithm for solving the problem. We suggest three models of berth assignment to minimizing the objective functions such as total port time, total berthing time and maximum berthing time by using a revised Maximum Position Shift(MPS) concept. The berth assignment problem is formulated by min-max and fuzzy 0-1 integer programming. Finally, we gave the numerical solutions of the illustrative examples.