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A SMOOTH PENALTY-FUNCTION ALGORITHM FOR NETWORK-STRUCTURED PROBLEMS
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DOI：10.1016/0377-2217(95)90601-A.png)
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摘要
En 中文
We discuss the design and implementation of an algorithm for the solution of large scale optimization problems with embedded network structures. The algorithm uses a linear-quadratic penalty (LQP) function to eliminate the side constraints and produces a differentiable, but non-separable, problem. A simplicial decomposition is subsequently used to decompose the problem into a sequence of linear network problems. Numerical issues and implementation details are also discussed. The algorithm is particularly suitable for vector architectures and was implemented on a CRAY Y-MP. We report very promising numerical results with a set of large linear multicommodity network flow problems drawn from a military planning application.
Keyword:
MULTICOMMODITY NETWORKS
NONLINEAR PROGRAMMING
LARGE-SCALE OPTIMIZATION
PENALTY METHODS
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6
论文数:
2.2W
被引数:
6.4W
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