A dynamic parameter encoding method was previously presented by Schraudolph and
Belew [J Mach Learn 9 (1992) 9] for solving optimizing problems using discrete zooming …

A new approach to optimization design concerning the configurations of structures using
genetic algorithm (GA) with a tournament selection strategy has been proposed. The …

This paper describes a new approach for reducing the number of the fitness function
evaluations required by a genetic algorithm (GA) for optimization problems with mixed …

The initial motivation for the development of algorithms inspired by biological principles of
evolution was the design and implementation of robust adaptive systems. Among the most …

Two strategies to improve the search ability of genetic algorithms (GA's) in large scale
optimization problems are presented. The first strategy is referred to as directed crossover …

A parameter‐less adaptive penalty scheme for genetic algorithms applied to constrained
optimization problems is proposed. Using feedback from the evolutionary process the …

Abstract The efficiency of Simple Genetic Algorithm (SGA) can be improved by some
strategies. They are elitest strategy, multi‐point crossover, identification of passive design …

Evolutionary structural optimization (ESO) is based on a simple idea that an optimal
structure (with maximum stiffness but minimum weight) can be achieved by gradually …

A flexible algorithm for solving nonlinear engineering design optimization problems
involving zero-one, discrete, and continuous variables is presented. The algorithm restricts …

During the last decade various methods have been proposed to handle linear and non‐
linear constraints by using genetic algorithms to solve problems of numerical optimization …