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Calculation Of Distance Of Underground Water Network Pipeline And Optimizated Arrangement

Posted on:2007-07-11Degree:MasterType:Thesis
Country:ChinaCandidate:S F LinFull Text:PDF
GTID:2132360185959359Subject:Computer application technology
Abstract/Summary:PDF Full Text Request
With the development of society, more and more water is needed. So it is required that a new pipeline will be inserted into the underground former-inserted complicated pipelines. We need to resolve the problem which how to do so that former-inserted pipelines isn't destructived. Calculate the distance between the new pipeline and the former-inserted pipelines(straight pipeline or curve pipeline) in the network, and judge whether the conflict generates between the new pipeline and the old pipelines. If the conflict not happened, we directly insert the new pipeline into the underground network. If the conflict happened, we insert the new pipeline with the rational (the water-prevented strength and the extravagance is both most small)bended degree into the underground network..The following five questions is mainly solved in the paper:(1) Use genetic algorithm to calculate the distance of the new pipeline and all the straight pipelines;(2) Use genetic algorithm to calculate the distance of the new pipeline and all the curve pipelines;(3) In order to avoid the collided dot ,use genetic algorithm to calculate the best height and radiu of inferior arc of the new pipeline;(4) Draw the plane and space graph of feed water network;(5) Construct the arrangement-optimizated system of underground network with Visual C++.Regarding the first question, a new genetic algorithm based on sort is proposed in the paper, and the effectiveness is proved by some examples. Two algorithms are advanced to solve the second question, one is the hybrid genetic algorithm of DCPM-FGA and descent local search, the other is that problem of both-object optimization is transited. Both of them is very...
Keywords/Search Tags:Feed water network, Optimizated arrangement, Genetic alogrithm, Genetic annealing alogrithm, Both-object optimization
PDF Full Text Request
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