Present paper is an application study of intuitionistic fuzzy optimization technique in agricultural production planning problem particularly a case of smallholder farmer in north Bihar, India. Generally, the crop planning problem is formulated as linear programming problems. but in realistic situation there are many uncertain factors in agricultural production planning problems and hence futur...

This paper shows how the simulated annealing (SA) algorithm provides a simple tool for solving fuzzy optimization problems. Often, the issue is not so much how to fuzzify or remove the conceptual imprecision, but which tools enable simple solutions for these intrinsically uncertain problems. A well-known linear programming example is used to discuss the suitability of the SA algorithm for solvi...

in this paper, a numerical method for nding minimal solution of a mn fullyfuzzy linear system of the form ax = b based on pseudo inverse calculation,is given when the central matrix of coecients is row full rank or column fullrank, and where a~ is a non-negative fuzzy mn matrix, the unknown vectorx is a vector consisting of n non-negative fuzzy numbers and the constant b isa vector consisti...

In this paper, we study the finitely many constraints of fuzzy relation inequalities problem and optimize the linear objective function on this region which is defined with fuzzy max-Lukasiewicz operator. In fact Lukasiewicz t-norm is one of the four basic t-norms. A new simplification technique is given to accelerate the resolution of the problem by removing the components having no effect on ...

LI, PINGKE. Fuzzy Relational Equations: Resolution and Optimization. (Under the direction of Professor Shu-Cherng Fang). Fuzzy relational equations play an important role as a platform in various applications of fuzzy sets and systems. The resolution and optimization of fuzzy relational equations are of our particular interests from both of the theoretical and applicational viewpoints. In this ...

This study introduces a fuzzy linear control design method for nonlinear systems with optimal H1 robustness performance. First, the Takagi and Sugeno fuzzy linear model is employed to approximate a nonlinear system. Next, based on the fuzzy linear model, a fuzzy controller is developed to stabilize the nonlinear system, and at the same time the effect of external disturbance on control performa...

We present a fuzzy optimization problem in business and economics. In this problem, a fuzzy price is determined by using a linear two degree demand functions. The objective is to find the optimal fuzzy revenue, which is derived from the fuzzy price. We use level (λ, 1) interval-valued fuzzy numbers to consider the fuzzy price and the fuzzy revenue. Using signed distance to defuzzify, we can obt...

Takagi–Sugeno (TS) fuzzy models can provide an effective representation of complex nonlinear systems in terms of fuzzy sets and fuzzy reasoning applied to a set of linear inputoutput submodels. In this paper, the TS fuzzy modeling approach is utilized to carry out the stability analysis and control design for nonlinear systems with actuator saturation. The TS fuzzy representation of a nonlinear...