From the user’s point of view, setting the parameters of a genetic algorithm (GA) is far from a trivial task. Moreover, the user is typically not interested in population sizes, crossover probabilities, selection rates, and other GA technicalities. He is just interested in solving a problem, and what he would really like to do, is to hand-in the problem to a blackbox algorithm, and simply press...

This paper presents a simple and easy implementable Least Mean Square (LMS) type approach for frequency estimation of three phase power system in an unbalanced condition. The proposed LMS type algorithm is based on a second order recursion for the complex voltage derived from Clarke's transformation which is proved in the paper. The proposed algorithm is real adaptive filter with real parameter...

Introduction: The selection of suitable beam angles and weights in external-beam radiotherapy is at present generally based upon the experience of the planner. Therefore, automated selection of beam angles and weights in forward-planned radiotherapy will be beneficial. Material and Methods: In this work, an efficient method is presented within the MATLAB environment to investigate how to improv...

Tuned mass dampers (TMDs) systems are one of the vibration controlled devices used to reduce the response of buildings subject to lateral loadings such as wind and earthquake loadings. Although TMDs system has received much attention from researchers due to their simplicity, the optimization of properties and placement of TMDs is a challenging task. Most research studies consider optimization o...

in this paper proposes a fuzzy multi-objective hybrid genetic and bee colony optimization algorithm(ga-bco) to find the optimal restoration of loads of power distribution network under fault.restoration of distribution systems is a complex combinatorial optimization problem that should beefficiently restored in reasonable time. to improve the efficiency of restoration and facilitate theactivity...

Genetic algorithm is one of the main heuristics that have been applied to scheduling problems in the last few decades. This paper presents a generalization of the genetic algorithm for solving project scheduling problem under time uncertainties within resource leveling technique. The generalization consists of handling fuzzy time parameter and fuzzy resource distribution instead of crisp ones. ...