EPANET Input Files of New York tunnels and Pacific City used in a metamodel-based optimization study

Metamodels have proven be very useful when it comes to reducing the computational requirements of Evolutionary Algorithm-based optimization by acting as quick-solving surrogates for slow-solving fitness functions. The relationship between metamodel scope and objective function varies between applications, that is, in some cases the metamodel acts as a surrogate for the whole fitness function, whereas in other cases it replaces only a component of the fitness function. This paper presents a formalized qualitative process to evaluate a fitness function to determine the most suitable metamodel scope so as to increase the likelihood of calibrating a high-fidelity metamodel and hence obtain good optimization results in a reasonable amount of time. The process is applied to the risk-based optimization of water distribution systems; a very computationally-intensive problem for real-world systems. The process is validated with a simple case study (modified New York Tunnels) and the power of metamodelling is demonstrated on a real-world case study (Pacific City) with a computational speed-up of several orders of magnitude.

Data and Resources

This dataset has no data

Cite this as

Broad, Darren R, Dandy, G C, Maier, H R (2015). Dataset: EPANET Input Files of New York tunnels and Pacific City used in a metamodel-based optimization study. https://doi.org/10.1594/PANGAEA.831723

DOI retrieved: 2015

Additional Info

Field Value
Imported on November 29, 2024
Last update November 29, 2024
License CC-BY-3.0
Source https://doi.org/10.1594/PANGAEA.831723
Author Broad, Darren R
Given Name Darren R
Family Name Broad
More Authors
Dandy, G C
Maier, H R
Source Creation 2015
Publication Year 2015
Subject Areas
Name: Ecology

Name: HumanDimensions

Related Identifiers
Title: A systematic approach to determining metamodel scope for risk-based optimization and its application to water distribution system design
Identifier: https://doi.org/10.1016/j.envsoft.2014.11.015
Type: DOI
Relation: IsSupplementTo
Year: 2015
Source: Environmental Modelling & Software
Authors: Broad Darren R , Dandy G C , Maier H R .