Applying Dynamic Surrogate Models in Noisy Genetic Algorithms to Optimize Groundwater Remediation Designs-Reference-Cited by-同舟云学术

Applying Dynamic Surrogate Models in Noisy Genetic Algorithms to Optimize Groundwater Remediation Designs

Published:2011-05 Issue:3 Volume:137 Page:284-292
ISSN:0733-9496
Container-title:Journal of Water Resources Planning and Management
language:en
Short-container-title:J. Water Resour. Plann. Manage.

Author:

Yan Shengquan¹²,Minsker Barbara¹²

Affiliation:

1. Senior Engineer, Microsoft Corporate, City Center Plaza, 555 110th Ave. NE, Bellevue, WA 98004, formerly Research Assistant, Dept. of Civil and Environmental Engineering, Univ. of Illinois, Urbana, IL. (corresponding author).

2. Professor, Dept. of Civil and Environmental Engineering, Univ. of Illinois, Urbana, IL.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Management, Monitoring, Policy and Law,Water Science and Technology,Geography, Planning and Development,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29WR.1943-5452.0000106

Reference36 articles.

1. Optimal design of aquifer cleanup systems under uncertainty using a neural network and a genetic algorithm

2. Stochastic management of pump-and-treat strategies using surrogate functions

3. Reducing Long-Term Remedial Costs by Transport Modeling Optimization

4. Robustness of the multiple realization method for stochastic hydraulic aquifer management

5. Partial Infeasibility Method for Chance‐Constrained Aquifer Management

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