Introduction to artificial life
Introduction to artificial life
Swarm intelligence
An Introduction to Genetic Algorithms
An Introduction to Genetic Algorithms
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
An Evolutionary Algorithm for Integer Programming
PPSN III Proceedings of the International Conference on Evolutionary Computation. The Third Conference on Parallel Problem Solving from Nature: Parallel Problem Solving from Nature
Ant Colony Optimization
Particle swarm approach for structural design optimization
Computers and Structures
Ant colony optimization of irregular steel frames including elemental warping effect
Advances in Engineering Software
Improved harmony search algorithms for sizing optimization of truss structures
Computers and Structures
Sizing truss structures using teaching-learning-based optimization
Computers and Structures
A survey of non-gradient optimization methods in structural engineering
Advances in Engineering Software
Hybrid fuzzy-genetic system for optimising cabled-truss structures
Advances in Engineering Software
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There is a noticeable increase in the emergence of non-deterministic search techniques that simulate natural phenomena into a numerical optimization technique in recent years. These techniques are used for developing structural optimization algorithms that are particularly effective for obtaining solutions to discrete programming problems. In this study amongst these techniques genetic algorithms, simulated annealing, evolution strategies, particle swarm optimizer, tabu search, ant colony optimization and harmony search are utilized to develop seven optimum design algorithms for real size rigidly connected steel frames. The design problems are formulated according to ASD-AISC (Allowable Stress Design Code of American Institute of Steel Institution).