Online surrogate multiobjective optimization algorithm for contaminated groundwater remediation designs

DOI10.1016/j.apm.2019.09.053zbMath1481.86005OpenAlexW2977887616WikidataQ127173168 ScholiaQ127173168MaRDI QIDQ1988875

Yanyan Li

Publication date: 24 April 2020

Published in: Applied Mathematical Modelling (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.apm.2019.09.053

zbMATH Keywords

multiobjective optimizationdense non-aqueous phase liquidgroundwater remediation designsmultiobjective feasibility-enhanced particle swarm optimization algorithmonline surrogate model-assisted framework

Mathematics Subject Classification ID

Applications of mathematical programming (90C90) Multi-objective and goal programming (90C29) Hydrology, hydrography, oceanography (86A05)

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Cites Work

• Approximating a finite element model by neural network prediction for facility optimization in groundwater engineering
• A hybrid particle swarm optimization with a feasibility-based rule for constrained optimization
• Shape optimization of structures with cutouts by an efficient approach based on XIGA and chaotic particle swarm optimization
• A fuzzy simulation-based optimization approach for groundwater remediation design at contaminated aquifers
• A novel characterization method of piezoelectric composite material based on particle swarm optimization algorithm
• A time-space Kriging-based sequential metamodeling approach for multi-objective crashworthiness optimization
• The construction and implementation of metamodels
• Adaptive Sampling Strategies for Stochastic Optimization
• Multi-objective feasibility enhanced particle swarm optimization

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