PARAMETER OPTIMIZATION FOR INTUITIONISTIC TRAPEZOIDAL FUZZY MODEL USING MULTIPLE OBJECTIVE PROGRAMMING METHOD

Author(s):  
YANNI WANG ◽  
YAPING DAI ◽  
KAORU HIROTA
2016 ◽  
Vol 7 (1) ◽  
pp. 104-118
Author(s):  
Tunjo Perić

Abstract Background: Vendor selection and supply quotas determination is one of the most important issues in the purchasing process in manufacturing. In many situations to solve this problem it is necessary to use the operations research methods. Objectives: This paper proposes a new methodology for vendor selection and determination of supplied quotas. The work investigates the problem of flour purchase by a company that manufactures bakery products. Methods/Approach: The problem is solved by using the model that combines a revised weighting method, and a multiple objective programming method based on game theory. The revised weighting method is used to determine the objective function coefficients, and a multiple objective programming method is used to select vendors and to determine supply quotas from the selected vendors. For selection of vendors and determination of quantities supplied by individual vendors three complex criteria are used: (1) purchasing costs, (2) product quality, and (3) vendor reliability. Results: The proposed methodology has numerous strengths, such as an efficient reduction of complex criteria functions to simple ones and efficient using of a new multiple objective programming methods based on cooperative game theory. Conclusions: The main advantage of the proposed approach is its efficiency and simplicity.


Author(s):  
JING-RUNG YU ◽  
GWO-HSHIUNG TZENG

This study proposes fuzzy multiple objective programming to determine the measure of fitness and the number of change-points in an interval piecewise regression model. To increase the measure of fitness, Tanaka and Lee proposed a conceptual procedure, which is a heuristic approach and becomes complicated for determining the proper polynomial. Therefore, a multiple objective approach is adopted to obtain a compromise solution among three objectives — maximizing the measure of fitness, minimizing the number of change-points and minimizing the width to obtain the interval regression models. By using the proposed method, a better measure of fitness can be obtained. Two numerical examples are used as demonstrations to illustrate our approach in more detail.


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