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    Data-level parallel linear-quadratic penalty algorithm for multicommodity network flows

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    Date Issued
    1994
    Author
    Pinar Mustafa, C.
    Zenios Stavros, A.
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    Please cite this item using this persistent URL
    http://hdl.handle.net/11693/25934
    Journal
    ACM Transactions on Mathematical Software
    Published as
    http://dx.doi.org/10.1145/198429.198439
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    • Research Paper [7145]
    Publisher
    ACM, New York, NY, United States
    Abstract
    We describe the development of a data-level, massively parallel software system for the solution of multicommodity network flow problems. Using a smooth linear-quadratic penalty (LQP) algorithm we transform the multicommodity network flow problem into a sequence of independent min-cost network flow subproblems. The solution of these problems is coordinated via a simple, dense, nonlinear master program to obtain a solution that is feasible within some user-specified tolerance to the original multicommodity network flow problem. Particular emphasis is placed on the mapping of both the subproblem and master problem data to the processing elements of a massively parallel computer, the Connection Machine CM-2. As a result of this design we can solve large and sparse optimization problems on current SIMD massively parallel architectures. Details of the implementation are reported, together with summary computational results with a set of test problems drawn from a Military Airlift Command application.

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    BİLKENT UNIVERSITY

    Copyright © Bilkent University - Library Technical Services | 06800 Bilkent, Ankara TURKEY
    If you have trouble accessing this page and need to request an alternate format, contact the webmaster. Phone: (312) 290 1771

    Contact Us | Send Feedback | Off-Campus Access