An interactive fuzzy multiple objective optimization method was proposed for solving fuzzy multiple objective linear programming problems where fuzzy parameters in both objective functions and constraints and fuzzy goals of objectives can be in any form of membership function. Based on the method, in this paper, a fuzzy multiple objective decision support system prototype is developed. A detail...

Most real world engineering design problems, such as cross-country water mains, include combinations of continuous, discrete, and binary value decision variables. Very often, the binary decision variables associate with the presence and/or absence of some nominated alternatives or project’s components. This study extends an existing continuous Ant Colony Optimization (ACO) algorithm to simultan...

Linear programming is one of the frequently applied tools in supply chain management. However, managers and decision makers may lack information about exact values of most of the parameters used in the optimization models. Fortunately, fuzzy linear programming comes up with a powerful tool to deal with this kind of incomplete data. In this paper, the flexible approach of fuzzy linear programmin...

`Abstract: -A fuzzy linear state estimation model is employed, which is based on Tanaka's fuzzy linear regression model, for modeling uncertainty in power system state estimation. Both measurements uncertainty as well as parametric uncertainty is considered by fuzzy estimator. The uncertain measurements and the parameters are expressed as fuzzy numbers with a triangular membership function that...

the fuzzy linear regression model with fuzzy input-output data andcrisp coefficients is studied in this paper. a linear programmingmodel based on goal programming is proposed to calculate theregression coefficients. in contrast with most of the previous works, theproposed model takes into account the centers of fuzzy data as animportant feature as well as their spreads in the procedure ofconstr...

in this paper, a new method is proposed to find the fuzzy optimal solution of fully fuzzy linear programming (abbreviated to fflp) problems. also, we employ linear programming (lp) with equality constraints to find a nonegative fuzzy number vector x which satisfies ax =b, where a is a fuzzy number matrix. then we investigate the existence of a positive solution of fully fuzzy linear system (ffls).

In this paper, bi-level linear programming problem with multiple objectives at each level in intuitionistic fuzzy environment is studied and solved. In this problem, technological coefficients and resources are characterized by intuitionistic fuzzy numbers having linear membership and non-membership function. Intuitionistic fuzzy efficient solution is computed for the upper level by the propose...

Abstract This paper investigates the problems of nonlinear channel equalization based on LMI-fuzzy methodology. According to Takagi-Sugeno (T-S) fuzzy modeling concept, the discrete-time nonlinear channel can be constructed by the piecewise linear subsystems. The FIR fuzzy equalizer design for nonlinear channel is transformed into a standard linear matrix inequality (LMI) optimization problem, ...

This paper describes a new methodology for the systematic design of fuzzy PID controllers based on theoretical fuzzy analysis and genetic-based optimization. An important feature of the proposed controller is its simple structure. It uses a one-input fuzzy inference with three rules and at most six tuning parameters. A closed-form solution for the control action is defined in terms of the nonli...

in structural time seriesregression models, binary (classic) dummy variables are used to quantify the effects of economic structural breaks, changes or qualitative variables. the binary dummy variable can be challenged using this dummy variable in which 0 or 1 represent absence or presence of structural breaks(or changes), but presence of the structural breaks(or changes) may not have uniform e...