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Ant Colony Optimization For Upgrading And Expansion Of Water Distribution System

Posted on:2007-11-11Degree:MasterType:Thesis
Country:ChinaCandidate:Y H ZhangFull Text:PDF
GTID:2132360182471896Subject:Municipal engineering
Abstract/Summary:PDF Full Text Request
Urban water network is an important part of the water-supply systems. According with the development of economic,expanding of city,the developing cities are facing the problem of upgrading and expansion of water distribution system.Because of the huge investment and management cost,optimal upgrading and expansion can save much money and actualize good ecnomic and social situation.The accomplishment of this paper is concerned with the practical water networks uprading and expansion engineering.Hydraulic modeling is the important foundation of the upgrading and expansion of water distribution system.Combining with real project . the preferable network mode) is obtained.It settled base of the upgrading and expansion of water distribution system. Because the simple loads optimal design for water supply is unreasonable, the multiple loads optimal design for water supply network systems is applied .Owing to the discrete character of the pipe diameter, with the object fuction being a multimodel function, and optimal upgrading and expansion being complex non-linear matter, genetic algorithm, simple ant colony optimization algorithm and improved ant colony optimization algorithm are seperataedly applied to a simple network optimization problem and the results obtained from improved ant colony optimization algorithm were better than those from the simple ACAAs and GA.Comparison of the optimal solution and the traditional solution of distribution system upgrading and expansion engineering in some city illustrates the optimal plan which applies improved ant colony Optimization algorithm saves the cost of water networks . furthermore,multiple loads optimal design for water supply network systems is better than simple load optimal design.
Keywords/Search Tags:water distribution system, upgrading and expansion, multiple loads design, genetic algorithms, ant colony optimization algorithms
PDF Full Text Request
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