Automatic calibration of urban drainage model using a novel multi-objective genetic algorithm

In order to successfully calibrate an urban drainage model, multiple calibration criteria should be considered. This raises the issue of adopting a method for comparing different solutions (parameter sets) according to a set of objectives. Amongst the global optimization techniques that have blossom...

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Bibliographic Details
Published in:Water science and technology 2005-01, Vol.52 (5), p.43-52
Main Authors: DI PIERRO, F, DIORDIEVIC, S, KAPELAN, Z, KHU, S.-T, SAVIC, D, WALTERS, G. A
Format: Article
Language:English
Subjects:
Algorithms
Applied sciences
Automation
Buildings. Public works
Calibration
Cities
Computation methods. Tables. Charts
Criteria
Drainage
Exact sciences and technology
Genetic algorithms
Mathematical models
Modelling
Multiple objective analysis
Pareto optimum
Sewage
Sewerage. Sewer construction
Solutions
Structural analysis. Stresses
Urban drainage
Waste Disposal, Fluid
Water Movements
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Summary:In order to successfully calibrate an urban drainage model, multiple calibration criteria should be considered. This raises the issue of adopting a method for comparing different solutions (parameter sets) according to a set of objectives. Amongst the global optimization techniques that have blossomed in recent years, Multi Objective Genetic Algorithms (MOGA) have proved effective in numerous engineering applications, including sewer network modelling. Most of the techniques rely on the condition of Pareto efficiency to compare different solutions. However, as the number of criteria increases, the ratio of Pareto optimal to feasible solutions increases as well. The pitfalls are twofold: the efficiency of the genetic algorithm search worsens and decision makers are presented with an overwhelming number of equally optimal solutions. This paper proposes a new MOGA, the Preference Ordering Genetic Algorithm, which alleviates the drawbacks of conventional Pareto-based methods. The efficacy of the algorithm is demonstrated on the calibration of a physically-based, distributed sewer network model and the results are compared with those obtained by NSGA-II, a widely used MOGA.
ISSN:0273-1223
1996-9732
DOI:10.2166/wst.2005.0105