A production inventory model with fuzzy coefficients using parametric geometric programming approach

Abstract

In general, cost constant parameters of inventory or production models are not rigid in real life rather these are imprecise in nature. In this paper we have presented imprecise cost constant parameters for an economic production quantity model. The unit production cost of this economic production quantity model is demand and reliability dependent. The imprecise parameters of the production model are considered as fuzzy in nature. The fuzzy model is solved by fuzzy parametric geometric programming technique. Finally, production model is numerically illustrated using fuzzy parametric geometric programming.

Fuzziness based sample categorization for classifier performance improvement

“…One can find many approaches from the existing references. For example, a multiple fuzzy NN classifier system based on mutual information and fuzzy integral [34], FPGP technique with parameters based on fuzzy coefficient [35], multilevel thresholding method based on maximum fuzzy entropy for extracting edge information [36] and classifying E-Health Projects based on advanced cluster techniques and fuzzy theories [37] have been proposed. A scheme to design adaptive output-feedback controller for uncertain nonlinear systems, where fuzzy logic systems are used to approximate the nonlinear function is proposed in [38].…”

Solving a posynomial geometric programming problem with fully fuzzy approach

“…They got optimal solution of the objective function directly without solving the equivalent transformed problem. They have also presented production inventory model with fuzzy coefficients using parametric geometric programming approach [18]. Mahapatra and Mahapatra [15] used fuzzy parametric geometric programming with cost constraint to find optimal reliability, and they have considered reliability series system with limited system cost as a constraint function [16].…”