Optimization Of Water Distribution Networks Using Genetic Algorithm
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Optimization Of Water Distribution Networks Using Genetic Algorithm
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Author : Gerçek Güç
language : en
Publisher: LAP Lambert Academic Publishing
Release Date : 2011-10
Optimization Of Water Distribution Networks Using Genetic Algorithm written by Gerçek Güç and has been published by LAP Lambert Academic Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-10 with categories.
This study gives a description about the development of a computer model, RealPipe, which relates genetic algorithm (GA) to the well known problem of least-cost design of water distribution network. GA methodology is an evolutionary process, basically imitating evolution process of nature. GA is essentially an efficient search method basically for nonlinear optimization cases. The genetic operations take place within the population of chromosomes. By means of various operators, the genetic knowledge in chromosomes change continuously and the success of the population progressively increases as a result of these operations. GA optimization is also well suited for optimization of water distribution systems, especially large and complex systems. The primary objective of this study is optimization of a water distribution network by GA. GA operations are realized on a special program developed by the author called RealPipe. RealPipe optimizes given water network distribution systems by considering capital cost of pipes only.
Production Well Operations Optimization In Water Distribution System Using Genetic Algorithm
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Author : Vineet Katiyar
language : en
Publisher:
Release Date : 2007
Production Well Operations Optimization In Water Distribution System Using Genetic Algorithm written by Vineet Katiyar and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with categories.
Storage And Pumping System Optimization Using Genetic Algorithms
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Author : Tobias A. Bloch
language : en
Publisher:
Release Date : 1998
Storage And Pumping System Optimization Using Genetic Algorithms written by Tobias A. Bloch and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with categories.
Water distributions systems generally do not operate at or their optimal points. The operational procedures of these systems should be reworked to make them more economically efficient. The ability to optimize (i.e., for economic efficiency) the operation of water distribution systems is hindered by the dimensionally (i.e., many different subsystems to optimize simultaneously) inherent in these systems. This is especially true for small time steps, pumping systems utilizing multiple pumps and distribution networks with multiple storage tanks. A branch of computer science called Genetic Algorithms has been shown to be very effective for optimizing complex systems. Genetic Algorithms are utilized in Two computer programs developed in this thesis. These programs were tested against simple water distribution systems and produced optimal solutions in a very short period of time. The architecture (i.e., program structure) for future computer programs that are based on the platform created in this thesis is also presented. These proposed versions should be useful in the optimization of large water distribution systems, something which has never been possible before.
Optimal Design Of Water Distribution Networks
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Author : Pramod R. Bhave
language : en
Publisher: Alpha Science Int'l Ltd.
Release Date : 2003
Optimal Design Of Water Distribution Networks written by Pramod R. Bhave and has been published by Alpha Science Int'l Ltd. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Science categories.
Design of water distribution networks is traditionally based on trial-and-approach in which the designer assumes, based on experience and judgment, sizes of different elements and successively modifies them until a network with satisfactory hydraulic performance is obtained. This text covers: Essential hydraulic, economic optimization principles. Theory is developed gradually for optimal design of simple, single-source branched networks subjected to single loading to complex, multiple-source looped networks subjected to multiple loading. Strengthening and expansion of existing networks and also reliability-based design. Several illustrative examples enabling the reader to apply them in practice- approximately 100 line drawings.
Maximum Entropy Based Evolutionary Optimization Of Water Distribution Networks Under Multiple Operating Conditions And Self Adaptive Search Space Reduction Method
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Author : Anna Marzena Czajkowska
language : en
Publisher:
Release Date : 2016
Maximum Entropy Based Evolutionary Optimization Of Water Distribution Networks Under Multiple Operating Conditions And Self Adaptive Search Space Reduction Method written by Anna Marzena Czajkowska and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with categories.
One of the complexities in designing WDN is evaluation of network performance. The accurate network performance measures such as reliability or failure tolerance are very time consuming calculations, thus surrogate measures are used for water distribution network (WDN) design optimization. Entropy is particularly advantageous since it involves only the flow in the pipe and the demands at the nodes. This thesis developed efficient new computational methods based on the maximum entropy formalism for the optimization of water distribution systems. Thus the maximum entropy based design approach has been extended here to include multiple operation conditions. Also, the path-related properties of the flow entropy have been exploited to develop a new self-adaptive approach for solution space reduction in multiobjective evolutionary optimization of water distribution systems that resulted in a significant reduction in the number of function evaluations required to find optimal and near optimal solutions. The novelty and originality of the current research are presented next. A new penalty-free multi-objective evolutionary optimization approach for the design of WDNs has been developed. It combines genetic algorithm with least cost design and maximum entropy. The approach can handle single operating conditions (SOC) as well as multiple operating conditions (MOC) for any given network. Previously, most of the work has been done for single loading patterns and it was assumed that nodal demands are constant. In reality nodal demand vary over the time so network designed to satisfy one operating condition might not be able to satisfy other loading patterns (i.e. pressure constraints might not be meet). The model has been applied to three well known water distribution networks. The approach has also been implemented on a large real-world network in the literature. Three different methods of designing for multiple loading patterns were investigated. Extensive testing proved that MOC outperform SOC in terms of hydraulic feasibility, pipe size distribution and reliability. The approach is computationally efficient and robust. The above mentioned penalty-free approach has been extended to form a module that would improve the convergence criteria of the GA by reducing its search space. For large real-world network GA might require extremely large number of function evaluations which could lead to delayed convergence. By reducing the search space, the GA's effectiveness and efficiency will increase as the algorithm will identify the solutions in smaller number of function evaluations. The search space reduction method presented herein is based on entropy and uses the importance of every path through network, which is an inherent property of the entropy function. The developed algorithm is dynamic, self-adaptive and does not require pre-defining the reduced sets of candidate diameters for each pipe. The method has been applied to a large network from the literature. Two cases were studied, one based on full search space and one for reduce search space (RSS) approach. Rapid stabilization was observed for the results obtained using RSS.
Optimization Of Municipal Water Supply Systems Using The Genetic Algorithm
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Author : Elizabeth Stuart Gibson
language : en
Publisher:
Release Date : 1994
Optimization Of Municipal Water Supply Systems Using The Genetic Algorithm written by Elizabeth Stuart Gibson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with Drinking water categories.
The Optimal Design Of Water Distribution Networks Using Genetic Algorithms
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Author : L. Murphy
language : en
Publisher:
Release Date : 1990
The Optimal Design Of Water Distribution Networks Using Genetic Algorithms written by L. Murphy and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990 with Water categories.
Water Distribution System Pumping Strategy Optimization By Genetic Algorithm
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Author : Mark William Wentzel
language : en
Publisher:
Release Date : 1993
Water Distribution System Pumping Strategy Optimization By Genetic Algorithm written by Mark William Wentzel and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993 with Water-supply engineering categories.
Optimisation Of Water Distribution Systems Using Genetic Algorithms For Hydraulic And Water Quality Issues
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Author : Christopher Michael Hewitson
language : en
Publisher:
Release Date : 1999
Optimisation Of Water Distribution Systems Using Genetic Algorithms For Hydraulic And Water Quality Issues written by Christopher Michael Hewitson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Hydraulics categories.
Develops a framework balancing water quality costs resulting from waterborne disease, disinfection by-product exposure and aesthetic concerns, against hydraulic costs, which include pipes, pumps and tanks. The genetic algorithms developed, successfully obtained the current optimal hydraulic solution, before adapting the model to incorporate water quality issues.
Computationally Intensive Design Of Water Distribution Systems
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Author : Manuel Alejandro Andrade-Rodriguez
language : en
Publisher:
Release Date : 2013
Computationally Intensive Design Of Water Distribution Systems written by Manuel Alejandro Andrade-Rodriguez and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with categories.
The burdensome capital cost of urban water distribution systems demands the use of efficient optimization methods capable of finding a relatively inexpensive design that guarantees a minimum functionality under all conditions of operation. The combinatorial and nonlinear nature of the optimization problem involved accepts no definitive method of solution. Adaptive search methods are well fitted for this type of problem (to which more formal methods cannot be applied), but their computational requirements demand the development and implementation of additional heuristics to find a satisfactory solution. This work seeks to employ adaptive search methods to enhance the search process used to find the optimal design of any water distribution system. A first study presented here introduces post-optimization heuristics that analyze the best design obtained by a genetic algorithm--arguably the most popular adaptive search method--and perform an ordered local search to maximize further cost savings. When used to analyze the best design found by a genetic algorithm, the proposed post-optimization heuristics method successfully achieved additional cost savings that the genetic algorithm failed to detect after an exhaustive search. The second study herein explores various ways to improve artificial neural networks employed as fast estimators of computationally intensive constraints. The study presents a new methodology for generating any large set of water supply networks to be used for the training of artificial neural networks. This dataset incorporates several distribution networks in the vicinity of the search space in which the genetic algorithm is expected to focus its search. The incorporation of these networks improved the accuracy of artificial neural networks trained with such a dataset. These neural networks consistently showed a lower margin of error than their counterparts trained with conventional training datasets populated by randomly generated distribution networks.