in the present paper, we study some properties of fuzzy norm of linear operators. at first the bounded inverse theorem on fuzzy normed linear spaces is investigated. then, we prove hahn banach theorem, uniform boundedness theorem and closed graph theorem on fuzzy normed linear spaces. finally the set of all compact operators on these spaces is studied.

The genetic algorithm has been widely used in many fields as an easy robust global search and optimization method. This paper introduces a new approach to find fuzzy rules using niche genetic algorithms with elitist migrating operator. It uses binary coding scheme. In order to make search results stable, elitist migrating operator reserves good individuals into an elitist sub-population. The si...

in this paper we present a method for solving fuzzy linear systemsby two crisp linear systems. also necessary and sufficient conditions for existenceof solution are given. some numerical examples illustrate the efficiencyof the method.

we present a new model and a new approach for solving fuzzylinear programming (flp) problems with various utilities for the satisfactionof the fuzzy constraints. the model, constructed as a multi-objective linearprogramming problem, provides flexibility for the decision maker (dm), andallows for the assignment of distinct weights to the constraints and the objectivefunction. the desired solutio...

Fuzziness is ever presented in real life decision making problems. In this paper, we adapt the pessimistic approach tostudy a pair of linear primal-dual problem under intuitionistic fuzzy (I-fuzzy) environment and prove certain dualityresults. We generate the duality results using exponential membership and non-membership functions to represent thedecision maker’s satisfaction and dissatisfacti...

Quite a few problems in production planning and scheduling, location, transportation, finance, and engineering design require that decisions be made under uncertainty. In this paper, we focus on Fuzzy nonlinear optimization problems in the Linear Fuzzy Real (LFR) numbers. The problems will consist of fuzzy constraints and objective functions, crisp constraints with a fuzzy objective function, o...

This paper presents a new controller for speed control problem of the BLDC motors. The nonlinear model of the motor is approximated by implementation of fuzzy rules. The uncertainties are considered in the fuzzy system. Using this model and linear matrix inequality (LMI) optimization, a robust controller for purpose of speed control of the motor has been designed and applied to it. The effectiv...

Abstract— This paper develops a solution procedure of multi-objective intuitionistic fuzzy optimization to solve a non-linear model with inexact co-efficient and resources. Interval approximation method is used here to convert the imprecise co-efficient which is a triangular fuzzy number to an interval number. We transform this interval number to a parametric interval valued functional form and...

This paper proposes a TSK-type Neuro-Fuzzy system tuned with a novel learning algorithm. The proposed algorithm used an improved version of the standard Particle Swarm Optimization algorithm, it employs several sub-swarms to explore the search space more efficiently. Each particle in a sub-swarm correct her position based on the best other positions, and the useful information is exchanged amon...