Comparison Between Two Multi-Objective Optimization Algorithms: PAES and MGDA. Testing MGDA on Kriging Metamodels

DOI10.1007/978-94-007-5288-7_13zbMath1270.65029OpenAlexW88038006MaRDI QIDQ2838342

Régis Duvigneau, Adrien Zerbinati, Jean-Antoine Désidéri

Publication date: 9 July 2013

Published in: Computational Methods in Applied Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-94-007-5288-7_13

zbMATH Keywords

multi-objective optimizationnumerical experimentsPareto setsteepest descent methodevolutionary strategiesderivative-free algorithmsgradient computationlocal finite differencesmultiple gradient descent algorithm

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Multi-objective and goal programming (90C29)

Related Items (4)

Meta-model-assisted MGDA for multi-objective functional optimization ⋮ Multiple-gradient descent algorithm (MGDA) for multiobjective optimization ⋮ Comparison Between Two Multi-Objective Optimization Algorithms: PAES and MGDA. Testing MGDA on Kriging Metamodels ⋮ Multiple-gradient Descent Algorithm for Pareto-Front Identification

Cites Work

• Comparison Between Two Multi-Objective Optimization Algorithms: PAES and MGDA. Testing MGDA on Kriging Metamodels
• Gmsh: A 3-D finite element mesh generator with built-in pre- and post-processing facilities

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