Real Coded Genetic Algorithm is the type of GA which operates on chromosomes with real valued parameters. Different mutation and crossover operations are defined for RCGA. One usable crossover for this kind of GA is to consider its chromosomes simply as bit strings and utilize same operations as Binary Coded GA. In this paper we attempt to show that this kind of crossover can not hasten the con...

This paper presents a real-coded genetic algorithm (RCGA) with new genetic operations (crossover and mutation). They are called the average-bound crossover (ABX) and wavelet mutation (WM). By introducing the proposed genetic operations, both the solution quality and stability are better than the RCGA with conventional genetic operations. A suite of benchmark test functions are used to evaluate ...

This paper proposes a superior Mixed Integer based hybrid Genetic Algorithm (MIGA) which inherits the advantages of binary and real coded Genetic Algorithm approach. The proposed algorithm is applied for the conventional generation cost minimization Optimal Power Flow (OPF) problem and for the Security Constrained Optimal Power Flow problem. Here, the main shortcoming with the conventional Gene...

Acknowledgements The production of this Toolbox was made possible by a UK SERC grant on " Genetic Algorithms in Control Systems Engineering " (GR/J17920). Many thanks are due to Hartmut Pohlheim, a visiting researcher from the Technical University Ilmenau, Germany, for the support for real-valued genetic algorithms and his hard work in coding and revising many of the routines in this Toolbox. T...

A method based on Electrical Capacitance Tomography (ECT) and an improved Least Squares Support Vector Machine (LS-SVM) is proposed for void fraction measurement of oil-gas two-phase flow. In the modeling stage, to solve the two problems in LS-SVM, pruning skills are employed to make LS-SVM sparse and robust; then the Real-Coded Genetic Algorithm is introduced to solve the difficult problem...

This paper presents new encoding methods for the binary genetic algorithm (BGA) and new converting methods for the real-coded genetic algorithm (RCGA). These methods are developed for the specific case in which some parameters have to be searched in wide ranges since their actual values are not known. The oversampling effect which occurs at large values in the wide range search are reduced by a...