Design of truss-structures for minimum weight using genetic algorithms
Finite Elements in Analysis and Design
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Evolutionary Algorithms for Solving Multi-Objective Problems
Evolutionary Algorithms for Solving Multi-Objective Problems
Multiple Objective Optimization with Vector Evaluated Genetic Algorithms
Proceedings of the 1st International Conference on Genetic Algorithms
Genetic Algorithms for Multiobjective Optimization: FormulationDiscussion and Generalization
Proceedings of the 5th International Conference on Genetic Algorithms
Evolutionary topological optimization of vibrating continuum structures for natural frequencies
Computers and Structures
Truss optimization with dynamic constraints using a particle swarm algorithm
Expert Systems with Applications: An International Journal
Structural and Multidisciplinary Optimization
Hierarchical stochastic metamodels based on moving least squares and polynomial chaos expansion
Structural and Multidisciplinary Optimization
Performance assessment of multiobjective optimizers: an analysis and review
IEEE Transactions on Evolutionary Computation
Symmetry and asymmetry of solutions in discrete variable structural optimization
Structural and Multidisciplinary Optimization
Hybrid fuzzy-genetic system for optimising cabled-truss structures
Advances in Engineering Software
Sensitivity analysis of fuzzy-genetic approach applied to cabled-truss design
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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This paper addresses single and multiobjective topology optimization of truss-like structures using genetic algorithms (GA's). In order to improve the performance of the GA's (despite the presence of binary topology variables) a novel approach based on kinematic stability repair (KSR) is proposed. The methodology consists of two parts, namely the creation of a number of kinematically stable individuals in the initial population (IP) and a chromosome repair procedure. The proposed method is developed for both 2D and 3D structures and is shown to produce (in the single-objective case) results which are better than, or equal to, those found in the literature, while significantly increasing the rate of convergence of the algorithm. In the multiobjective case, the proposed modifications produce superior results compared to the unmodified GA. Finally the algorithm is successfully applied to a cantilevered 3D structure.