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    Deterministic Integrated Optimization Model for Sewage Collection Networks Using Tabu Search

    Source: Journal of Water Resources Planning and Management:;2015:;Volume ( 141 ):;issue: 001
    Author:
    Ali Haghighi
    ,
    Amin E. Bakhshipour
    DOI: 10.1061/(ASCE)WR.1943-5452.0000435
    Publisher: American Society of Civil Engineers
    Abstract: This paper presents an integrated optimization model for designing sewage collection networks. The layout configuration is designed using the loop-by-loop cutting algorithm. Then, the network with a given layout is hydraulically designed to determine sewer diameters, installation depths, and pump specifications. In both design steps, all technical constraints and criteria are systematically satisfied. Thereby, the optimization of sewer systems becomes totally unconstrained for the applied optimization solver. In this problem, the objective function is the network’s construction cost and the decision variables are the parameters of layout generation and sewer specifications. For optimization of the cost function, the tabu search (TS) method as a deterministic combinatorial metaheuristic is developed and coupled to the design solvers. The proposed scheme is able to search adaptively in feasible parts of the problem’s decision space as well as to solve the two subproblems of layout generation and sewer sizing simultaneously. Then the model is applied against a benchmark case study. It is found that using the integrated model, the design of sewer networks becomes computationally more efficient and systematic, and it is a very promising approach to attain the global optima.
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      Deterministic Integrated Optimization Model for Sewage Collection Networks Using Tabu Search

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    http://yetl.yabesh.ir/yetl1/handle/yetl/71778
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    • Journal of Water Resources Planning and Management

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    contributor authorAli Haghighi
    contributor authorAmin E. Bakhshipour
    date accessioned2017-05-08T22:07:24Z
    date available2017-05-08T22:07:24Z
    date copyrightJanuary 2015
    date issued2015
    identifier other29780545.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/71778
    description abstractThis paper presents an integrated optimization model for designing sewage collection networks. The layout configuration is designed using the loop-by-loop cutting algorithm. Then, the network with a given layout is hydraulically designed to determine sewer diameters, installation depths, and pump specifications. In both design steps, all technical constraints and criteria are systematically satisfied. Thereby, the optimization of sewer systems becomes totally unconstrained for the applied optimization solver. In this problem, the objective function is the network’s construction cost and the decision variables are the parameters of layout generation and sewer specifications. For optimization of the cost function, the tabu search (TS) method as a deterministic combinatorial metaheuristic is developed and coupled to the design solvers. The proposed scheme is able to search adaptively in feasible parts of the problem’s decision space as well as to solve the two subproblems of layout generation and sewer sizing simultaneously. Then the model is applied against a benchmark case study. It is found that using the integrated model, the design of sewer networks becomes computationally more efficient and systematic, and it is a very promising approach to attain the global optima.
    publisherAmerican Society of Civil Engineers
    titleDeterministic Integrated Optimization Model for Sewage Collection Networks Using Tabu Search
    typeJournal Paper
    journal volume141
    journal issue1
    journal titleJournal of Water Resources Planning and Management
    identifier doi10.1061/(ASCE)WR.1943-5452.0000435
    treeJournal of Water Resources Planning and Management:;2015:;Volume ( 141 ):;issue: 001
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian