Multidisciplinary optimization of a transport aircraft wing using particle swarm optimization

By Gerhard Venter, J. Sobieszczanski-Sobieski. 2002

350 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/d0ff2d924242a3a8d1826faf0b577e1f09411423

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In Artificial Intelligence

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Citations in the corpus

pyOpt: a Python-based object-oriented framework for nonlinear constrained optimization (2011, positive): “Other versions of particle swarm algorithms have also been used to optimize aircraft structures (Venter and Sobieszczanski-Sobieski 2004).”
Parallel global optimization with the particle swarm algorithm (2004, background): “It has been successfully applied to largescale problems [5, 6, 7] in several engineering disciplines and, being a population based approach, is readily parallelizable.”
Particle Swarm Optimization in Structural Design (2007, background): “By doing so, the objective function is reduced while the particle is pointed back towards the feasible region of the design space (Venter & Sobieszczanski-Sobieski, 2004).”
Interval dynamic response analysis of vehicle-bridge interaction system with uncertainty (2013, methodology): “Although PSO has attracted comprehensive attention and has been applied in many areas, very little research has been conducted for solving structural optimization problems [23–26].”
Mathematical and Metaheuristic Applications in Design Optimization of Steel Frame Structures: An Extensive Review (2013, methodology): “The steps of the algorithm are outlined in the following as given in [177, 178].”
A study of particle swarm optimization particle trajectories (2006, background): “While static inertia values have been used successfully, adaptive inertia values have also shown to lead to convergent behaviour [25] [30] [5] [24] [17] [28].”
New global optimization methods for ship design problems (2009, methodology): “We draw inspiration from Particle Swarm Optimization (PSO) methods because they are widely used for solving many industrial and engineering problems even though they have poor if no theoretical foundations (see for instance Venter and Sobieszczanski-Sobieski 2003, 2004; Pinto et al. 2004).”