Parameter Selection in Particle Swarm Optimization
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
Evolutionary Optimization Versus Particle Swarm Optimization: Philosophy and Performance Differences
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
A discrete particle swarm optimization algorithm for the no-wait flowshop scheduling problem
Computers and Operations Research
A heuristic particle swarm optimization method for truss structures with discrete variables
Computers and Structures
Structural topology optimization using ant colony optimization algorithm
Applied Soft Computing
On the usefulness of non-gradient approaches in topology optimization
Structural and Multidisciplinary Optimization
A survey of non-gradient optimization methods in structural engineering
Advances in Engineering Software
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The particle swarm optimization (PSO) algorithm, a relatively recent bio-inspired approach to solve combinatorial optimization problems mimicking the social behavior of birds flocking, is applied to problems of continuum structural topology design for the purpose of investigating optimal topologies and automatically creating innovative solutions. An overview of the PSO and binary PSO algorithms are first described. A discretized topology design representation and the method for mapping binary particle into this representation are then detailed. Subsequently, a modified binary PSO algorithm that adopts the concept of genotype-phenotype representation is illustrated. Several well-studied examples from structural topology optimization problems of minimum weight and minimum compliance are used to demonstrate its efficiency and versatility. The results indicate the effectiveness of the proposed algorithm and its ability to find families of structural topologies.