Meta-model-assisted MGDA for multi-objective functional optimization

DOI10.1016/j.compfluid.2014.06.018zbMath1390.74164OpenAlexW1970522654MaRDI QIDQ1641565

Imane Ghazlane, Andrea Minelli, Adrien Zerbinati, Jean-Antoine Désidéri

Publication date: 19 June 2018

Published in: Computers and Fluids (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.compfluid.2014.06.018

zbMATH Keywords

numerical methodsPareto optimalitydrag reductionsonic boomcompressible aerodynamicsdifferentiable optimizationmulti-objective optimum-shape design

Mathematics Subject Classification ID

Multi-objective and goal programming (90C29) Fluid-solid interactions (including aero- and hydro-elasticity, porosity, etc.) (74F10) General aerodynamics and subsonic flows (76G25) Topological methods for optimization problems in solid mechanics (74P15)

Related Items (2)

Gradient based biobjective shape optimization to improve reliability and cost of ceramic components ⋮ Expedited constrained multi-objective aerodynamic shape optimization by means of physics-based surrogates

Uses Software

• SPEA2
• FUN3D

Cites Work

• Multiple-gradient descent algorithm (MGDA) for multiobjective optimization
• Nonlinear multiobjective optimization
• Comparison Between Two Multi-Objective Optimization Algorithms: PAES and MGDA. Testing MGDA on Kriging Metamodels
• Drag/thrust analysis of jet-propelled transonic transport aircraft; Definition of physical drag components
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