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...

In this paper, a new improved Differential Search Algorithm optimization approach is proposed and successfully applied to the design and tuning of a PID-type Fuzzy Logic Controller. The scaling factors tuning problem of the Fuzzy Logic Controller structure is formulated and systematically resolved, using the improved constrained Differential Search Algorithm-based method. A comparison, with the...

In this paper we consider a global optimization approach for solving fuzzy fractional posynomial geometric programming problems. The problem of concern involves positive trapezoidal fuzzy numbers in the objective function. For obtaining an optimal solution, Dinkelbach’s algorithm which achieves the optimal solution of the optimization problem by means of solving a sequence of subproblems ...

Ant colony optimization algorithm is a heuristic approach for the solution of combinatorial optimization problems. In order to solve continuous optimization models, an ant colony optimization algorithm is designed. Based on this algorithm, two hybrid intelligent algorithms combined with fuzzy simulation and neural network or integral sum approximation are introduced for solving fuzzy expected v...

Trial and error method can be used to find a suitable design of a fuzzy controller. Generally, the design of fuzzy controller involves determination of the fuzzy rules, Membership Functions (MFs) and scaling factors. An optimization algorithm facilitates the design process and finds an optimal design to achieve a desired performance. This paper presents an Improved Bacterial Foraging Optimizati...

This paper presents a Genetic Algorithm (GA) approach for solving constrained reliability optimization problem of the five unit bridge network. Considering uncertainty for cost, the reliability optimization problem has been solved by GA technique to maximize system reliability. GA is an efficient method for solving this type of optimization problems. This paper successfully applies the GA techn...

in this paper, the finitely many constraints of a fuzzy relationinequalities problem are studied and the linear objective function on the regiondefined by a fuzzy max-average operator is optimized. a new simplificationtechnique which accelerates the resolution of the problem by removing thecomponents having no effect on the solution process is given together with analgorithm and a numerical exa...

In this paper, a special class of redundancy optimization problem with fuzzy random variables is presented. In this model, fuzzy random lifetimes are considered as basic parameters and the Er-expected of system lifetime is used as a major type of system performance. Then a redundancy optimization problem is formulated as a binary integer programming model. Furthermore, illustrative numerical ex...

− A new trend in the design of fuzzy rulebased systems is the use of evolutionary multiobjective optimization (EMO) algorithms. This trend is observed in various areas in machine learning. EMO algorithms are often used to search for a number of Pareto-optimal non-linear systems with respect to their accuracy and complexity. In this paper, we first explain some basic concepts in multiobjective o...