Real-coded genetic algorithm parameter setting for water distribution system optimisation.
Date
2008
Authors
Gibbs, Matthew S.
Editors
Advisors
Maier, Holger R.
Dandy, Graeme Clyde
Dandy, Graeme Clyde
Journal Title
Journal ISSN
Volume Title
Type:
Thesis
Citation
Statement of Responsibility
Conference Name
Abstract
The management of Water Distribution Systems (WDSs) involves making decisions about
various operations in the network, including the scheduling of pump operations and setting
of disinfectant dosing rates. There are often conflicting objectives in making these
operational decisions, such as minimising costs while maximising the quality of the water
supplied. Hence, the operation of WDSs can be very difficult, and there is generally considerable
scope to improve the operational efficiency of these systems by improving the
associated decision making process. In order to achieve this goal, optimisation methods
known as Genetic Algorithms (GAs) have been successfully adopted to assist in determining
the best possible solutions to WDS optimisation problems for a number of years.
Even though there has been extensive research demonstrating the potential of GAs for
improving the design and operation of WDSs, the method has not been widely adopted
in practice. There are a number of reasons that may contribute to this lack of uptake,
including the following difficulties: (a) developing an appropriate fitness function that is
a suitable description of the objective of the optimisation including all constraints, (b)
making decisions that are required to select the most appropriate variant of the algorithm,
(c) determining the most appropriate parameter settings for the algorithm, and (d) a reluctance
of WDS operators to accept new methods and approaches.
While these are all important considerations, the correct selection of GA parameter values
is addressed in this thesis. Common parameters include population size, probability of
crossover, and probability of mutation. Generally, the most suitable GA parameters must
be found for each individual optimisation problem, and therefore it might be expected that
the best parameter values would be related to the characteristics of the associated fitness
function.
The result from the work undertaken in this thesis is a complete GA calibration methodology,
based on the characteristics of the optimisation problem. The only input required
by the user is the time available before a solution is required, which is beneficial in the WDS operation optimisation application considered, as well as many others where computationally
demanding model simulations are required. Two methodologies are proposed
and evaluated in this thesis, one that considers the selection pressure based on the characteristics
of the fitness function, and another that is derived from the time to convergence
based on genetic drift, and therefore does not require any information about the fitness
function characteristics.
The proposed methodologies have been compared against other GA calibration methodologies
that have been proposed, as well as typical parameter values to determine the most
suitable method to determine the GA parameter values. A suite of test functions has been
used for the comparison, including 20 complex mathematical optimisation problems with
different characteristics, as well as realistic WDS applications.
Two WDS applications have been considered: one that has previously been optimised in
the literature, the Cherry Hills-Brushy Plains network; and a real case study located in
Sydney, Australia. The optimisation problem for the latter case study is to minimise the
pumping costs involved in operating the WDS, subject to constraints on the system, including
minimum disinfectant concentrations. Of the GA calibration methods compared,
the proposed calibration methodology that considered selection pressure determined the
best solution to the problem, producing a 30% reduction in the electricity costs for the
water utility operating the WDS.
The comparison of the different calibration approaches demonstrates three main results:
1. that the proposed methodology produced the best results out of the different GA
calibration methods compared;
2. that the proposed methodology can be applied in practice; and
3. that a correctly calibrated GA is very beneficial when solutions are required in a
limited timeframe.
School/Discipline
School of Civil, Environmental and Mining Engineering
Dissertation Note
Thesis (Ph.D.) - University of Adelaide, School of Civil, Environmental and Mining Engineering, 2008
Provenance
Copyright material removed from digital thesis. See print copy in University of Adelaide Library for full text.