Comparing solutions under uncertainty in multiobjective optimization

DOI10.1155/2014/817964zbMath1407.90299OpenAlexW2015135818WikidataQ59069561 ScholiaQ59069561MaRDI QIDQ1719201

Bogdan Filipič, Miha Mlakar, Tea Tušar

Publication date: 8 February 2019

Published in: Mathematical Problems in Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2014/817964

Mathematics Subject Classification ID

Multi-objective and goal programming (90C29) Sensitivity, stability, parametric optimization (90C31)

Related Items (3)

Surrogate-assisted bounding-box approach for optimization problems with tunable objectives fidelity ⋮ Non-parametric measure approximations for constrained multi-objective optimisation under uncertainty ⋮ An adaptive strategy on the error of the objective functions for uncertainty-based derivative-free optimization

Cites Work

• Hybridization of a multi-objective genetic algorithm, a neural network and a classical optimizer for a complex design problem in fluid dynamics
• Unnamed Item
• Unnamed Item

This page was built for publication: Comparing solutions under uncertainty in multiobjective optimization