In view of the conservatism of the conventional linear matrix inequality (LMI) based fault detection observer design for Takagi-Sugeno fuzzy nonlinear systems with more If-Then rules, an improved fuzzy observer design is presented. The identical transformation of matrix inequalities is employed to reduce the conservatism and the number of LMI constraints, which can accommodate to the models wit...

Multiobjective genetic fuzzy rule selection is based on the generation of a set of candidate fuzzy classification rules using a preestablished granularity or multiple fuzzy partitions with different granularities for each attribute. Then, a multiobjective evolutionary algorithm is applied to perform fuzzy rule selection. Since using multiple granularities for the same attribute has been sometim...

In this paper attention has been paid to the study of multiobjective linear fractional programming problem (MOLFPP) by using fuzzy set theoretic approach. In this approach, MOLFPP is transformed into multiobjective linear programming problem (MOLPP) by suitable transformation. In algorithm-I, MOLFPP is transformed into MOLPP by using fuzzy set theory and the pareto optimal solution of the trans...

It is with a great significance to discuss the selection model of regional strategic emerging industry. First, the paper uses the fuzzy optimization theory to select the central industry of area as the regional strategic emerging industry and try to optimize the weight’s calculation in the multistage fuzzy comprehensive evaluation to get more accurate results. Then it will do a strategic emergi...

The optimality conditions for linear programming problems with fuzzy coefficients are derived in this paper. Two solution concepts are proposed by considering the orderings on the set of all fuzzy numbers. The solution concepts proposed in this paper will follow from the similar solution concept, called the nondominated solution, in the multiobjective programming problem. Under these settings, ...

The paper presents FMOPSO a multiobjective optimization method that uses a Particle Swarm Optimization algorithm enhanced with a Fuzzy Logic-based controller. Our implementation makes use of a number of fuzzy rules as well as dynamic membership functions to evaluate search spaces at each iteration. The method works based on Pareto dominance and was tested using standard benchmark data sets. Our...

This paper presents the solution of environmental/ economic dispatch (EED) problem by using a multiobjective bees algorithm (MBA) with clustering technique. EED problem is to minimize simultaneously the total fuel cost and environmental pollution of generation while satisfying various constrains. The MBA is modified from Bees Algorithm in order to solve EED problem through compromised fuzzy and...

Portfolio selection is a usual multiobjective problem. This paper will try to deal with the optimum portfolio for a private investor, taking into account three criteria: return, risk and liquidity. These objectives, in general, are not crisp from the point of view of the investor, so we will deal with them in fuzzy terms. The problem formulation is a goal programming (G.P.) one, where the goals...