Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
Numerical Optimization of Computer Models
Numerical Optimization of Computer Models
The optimisation of space structures using evolution strategies with functional networks
Engineering with Computers
Advances in Engineering Software - Special issue on evolutionary optimization of engineering problems
An overview of evolutionary algorithms for parameter optimization
Evolutionary Computation
Structure assembling by stochastic topology optimization
Computers and Structures
General purpose software for efficient uncertainty management of large finite element models
Finite Elements in Analysis and Design
An exponential big bang-big crunch algorithm for discrete design optimization of steel frames
Computers and Structures
A survey of non-gradient optimization methods in structural engineering
Advances in Engineering Software
Fully Stressed Design Evolution Strategy for Shape and Size Optimization of Truss Structures
Computers and Structures
A bat-inspired algorithm for structural optimization
Computers and Structures
A bi-level hierarchical method for shape and member sizing optimization of steel truss structures
Computers and Structures
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In this study the computational performance of adaptive evolution strategies (ESs) in large-scale structural optimization is mainly investigated to achieve the following objectives: (i) to present an ESs based solution algorithm for efficient optimum design of large structural systems consisting of continuous, discrete and mixed design variables; (ii) to integrate new parameters and methodologies into adaptive ESs to improve the computational performance of the algorithm; and (iii) to assess successful self-adaptation models of ESs in continuous and discrete structural optimizations. A numerical example taken from the literature is studied in depth to verify the enhanced performance of the algorithm, as well as to scrutinize the role and significance of self-adaptation in ESs for a successfully implemented optimization process. Besides, the utility of the algorithm for practical structural engineering applications is demonstrated using a bridge design example. It is shown that adaptive ESs are reliable and powerful tools, and well-suited for optimum design of complex structural systems, including large-scale structural optimization.