## Abstract

Most large-scale optimization problems exhibit structures that allow the possibility of attack via algorithms that exhibit a high level of parallelism. The emphasis of this paper is the development of parallel optimization algorithms for a class of convex, block-structured problems. Computational experience is cited for some large-scale problems arising from traffic assignment applications. The algorithms considered here have the property that they allow such problems to be decomposed into a set of smaller optimization problems at each major iteration. These smaller problems correspond to linear single-commodity networks in the traffic assignment case, and they may be solved in parallel. Results are given for the distributed solution of such problems on the CRYSTAL multicomputer.

Original language | English |
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Pages (from-to) | 327-345 |

Number of pages | 19 |

Journal | Mathematical Programming, Series B |

Volume | 42 |

Issue number | 1-3 |

DOIs | |

State | Published - 1 Apr 1988 |