The genetic algorithm (GA) is an evolutionary optimization algorithm operating based upon reproduction, crossover and mutation. On the other hand, particle swarm optimization (PSO) is a swarm intelligence algorithm functioning by means of inertia weight, learning factors and the mutation probability based upon fuzzy rules. In this paper, particle swarm optimization in association with genetic a...

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...

The optimization of a Fuzzy Cognitive Map model for the supervision and monitoring of the radiotherapy process is proposed. This is performed through the minimization of the corresponding objective function by using the Particle Swarm Optimization and the Differential Evolution algorithms. The proposed approach determines the cause–effect relationships among the concepts of the supervisor–Fuzzy...

the concept of intelligently controlling the search process of gravitational search algorithm (gsa) is introduced to develop a novel data mining technique. the proposed method is called fuzzy gsa miner (fgsa-miner). at first a fuzzy controller is designed for adaptively controlling the gravitational coefficient and the number of effective objects, as two important parameters which play major ro...

This paper discussed the implementation of Particle Swarm Optimization (PSO) to optimize a Fuzzy Model Reference Learning Controller (FMRLC) for tanker ship. FMRLC is developed by synthesizing several basic ideas from fuzzy set and control theory. It can achieve the heading regulation of tanker ship exposed to plant changes and disturbances by adjusting the rules in a direct fuzzy controller so...

In this paper, a discrete particle swarm optimization method is proposed to solve the multi-objective task assignment problem in distributed environment. The objectives of optimization include the makespan for task execution and the budget caused by resource occupation. A two-stage approach is designed as follows. In the first stage, several artificial particles are added into the initialized s...

This paper illustrates the importance of controllers on energy saving opportunity of a partially loaded three-phase induction motor drive in variable load and speed applications. An overview of various controllers: loss model controller, search controller and their hybridization are given. Fuzzy Pre-Compensated Proportional Integral (FPPI) is used to improve motor‟s dynamic performances during ...