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University of Illinois at Urbana-Champaign
A Self -Adaptive Hybrid Genetic Algorithm for Optimal Groundwater Remediation Design
Abstract
dc:descriptionThe application of the e-SAHGA algorithm to a hypothetical groundwater remediation design problem showed 90% reliability in identifying the solution faster than the SGA, with average savings of 64% across 100 runs with different random initial populations. Finally, e-SAHGA was tested on a field-scale remediation design problem, re-evaluation of the remediation system for Umatilla Army Depot, where it gave computational savings between 30% and 60% and, for one solution method, found a solution that was 4% better than the one found by the SGA.
Degree
thesis:*- Name thesis:degree_name
- Ph.D.
- Level thesis:degree_level
- Dissertation
- Discipline thesis:degree_discipline
- Civl and Environmental Engineering
- Grantor
- University of Illinois at Urbana-Champaign
- Year dc:date
- 2015
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Espinoza, Felipe Patricio
- Contributors dc:contributor
-
- Minsker, Barbara S.
Subjects
dc:subject × 1Rights
- Language dc:language
- eng
Identifiers
dc:identifier.*- Identifier
- (MiAaPQ)AAI3101832
- OAI identifier oai:identifier
- oai:www.ideals.illinois.edu:2142/83212