A data-level parallel linear-quadratic penalty algorithm for multicommodity network flows

Date
1994
Authors
Pinar, M. C.
Zenios, S. A.
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Source Title
ACM Transactions on Mathematical Software
Print ISSN
0098-3500
Electronic ISSN
Publisher
Association for Computing Machinery
Volume
20
Issue
4
Pages
531 - 552
Language
English
Type
Article
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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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Keywords
Computer architecture, Computer systems programming, Constraint theory, Mathematical programming, Optimization, Parallel algorithms, Parallel processing systems, Multicommodity network problems, Parallel linear quadratic penalty algorithm, Parallel optimization, Algorithms
Citation
Published Version (Please cite this version)