In this paper a general bottleneck combinatorial optimization problem with uncertain element weights modeled by fuzzy intervals is considered. A rigorous possibilistic formalization of the problem and solution concepts in this setting that lead to finding robust solutions under fuzzy weights are given. Some algorithms for finding a solution according to the introduced concepts and evaluating op...

in most industrial zones, electric energy is one of the most important energy sources. since electrical motors are the main energy consumers of industrial factories, consumption optimization in these motors can be considered as a main option related to energy saving. one very effective way to reduce the consumption of these equipment is to use a motor speed controllers or drives. since the loss...

The aim of his paper is to present some applications of fuzzy techniques in the optimization-based design of analog circuits. Our approach turns into profit the advantages offered by different fuzzy techniques. Fuzzy systems or fuzzy sets are involved in every algorithm phase. The optimization problem formulation is accomplished in a flexible manner using fuzzy sets to define fuzzy optimization...

• J. Beringer and E. Hüllermeier. Efficient instance based learning on data streams. Adaptive optimization of the number of clusters in fuzzy clustering. Fuzzy clustering of parallel data streams. Adaptive optimization of the number of clusters in fuzzy clustering.

Despite convex mathematical optimization methods be applied to general linear optimization problems it can also be applied in a special class of nonlinear optimization. As ambiguity and vagueness are natural and ever-present in real-life situations requiring solutions, it makes perfect sense to attempt to address them using fuzzy convex optimization. In this work, two fuzzy convex approaches ba...

This paper proposes a swarm optimized fuzzy logic based power system stabilizer (SFLPSS). The fuzzy logic stabilizer membership functions parameters, inputs and outputs gains and fuzzy rules are tuned and optimized using particle swarm optimization (PSO) technique. Optimization parameters were subject to realistic constraint. The optimization is done using a seventh order nonlinear model of a s...

In fuzzy optimization it is desirable that all fuzzy solutions under consideration be attainable, so that the decision maker will be able to make ‘‘a posteriori’’ decisions according to current decision environments. No additional optimization runs will be needed when the decision environment changes or when the decision maker needs to evaluate several decisions to establish the most appropriat...

Inventory management studies to minimize the average total cost per unit time and to determine the quantity of the stocked material to be ordered. In this paper the demand follows normal distributive under deterministic, stochastic and mixed environment, respectively and thus the model becomes more realistic. Expected annual cost is measured, with varying defective rate. After that the item wis...

As we all know, the parameter optimization of Mamdani model has a defect of easily falling into local optimum. To solve this problem, we propose a new algorithm by constructing Mamdani Fuzzy neural networks. This new scheme uses fuzzy clustering based on particle swarm optimization (PSO) algorithm to determine initial parameter of Mamdani Fuzzy neural networks. Then it adopts PSO algorithm to o...

This paper gives the structure optimization of fuzzy control systems based on genetic algorithm in the MATLAB environment. The genetic algorithm is a powerful tool for structure optimization of the fuzzy controllers, therefore, in this paper, integration and synthesis of fuzzy logic and genetic algorithm has been proposed. The genetic algorithms are applied for fuzzy rules set, scaling factors ...