New Generation Gap Models for Evolutionary Algorithm in Real Parameter Optimization

A Computationally EÆ ient Evolutionary Algorithm for Real-Parameter Optimization

A Computationally Efficient Evolutionary Algorithm for Real-Parameter Optimization

Due to increasing interest in solving real-world optimization problems using evolutionary algorithms (EAs), researchers have recently developed a number of real-parameter genetic algorithms (GAs). In these studies, the main research effort is spent on developing an efficient recombination operator. Such recombination operators use probability distributions around the parent solutions to create ...

Recent Advances in Real-Parameter Evolutionary Algorithm

Feasibility Preserving Constraint-Handling Strategies for Real Parameter Evolutionary Optimization

Evolutionary Algorithms (EAs) are being routinely applied for a variety of optimization tasks, and real-parameter optimization in the presence of constraints is one such important area. During constrained optimization EAs often create solutions that fall outside the feasible region; hence a viable constrainthandling strategy is needed. This paper focuses on the class of constraint-handling stra...

A Differential Covariance Matrix Adaptation Evolutionary Algorithm for real parameter optimization

Hybridization in context to Evolutionary Computation (EC) aims at combining the operators and methodologies from different EC paradigms to form a single algorithm that may enjoy a statistically superior performance on a wide variety of optimization problems. In this article we propose an efficient hybrid evolutionary algorithm that embeds the difference vector-based mutation scheme, the crossov...