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Nonlinear network optimization on a massively parallel connection machine

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Lagrangian dual coordinatewise maximization algorithm for network transportation problems with quadratic costs

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Linear and Nonlinear Programming

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Parallel successive overrelaxation methods for symmetric linear complementarity problems and linear programs

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A unified framework for primal-dual methods in minimum cost network flow problems

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Parallel optimization for traffic assignment

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Vectorization and multitasking of nonlinear network programming algorithms

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Relaxation techniques for strictly convex network problems

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A parallel algorithm for solving the linear complementarity problem

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A parallel algorithm for generalized networks

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Convergence theories of distributed iterative processes: A survey

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Chaotic relaxation

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A distributed algorithm for convex network optimization problems

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Linear and nonlinear programming.

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Distributed Asynchronous Relaxation Methods for Linear Network Flow Problems

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The Connection Machine

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A distributed asynchronous relaxation algorithm for the assignment problem

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A Class of Decentralized Routing Algorithms Using Relaxation

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Distributed Asynchronous Relaxation Methods for Convex Network Flow Problems

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Relaxation Methods for Network Flow Problems with Convex Arc Costs

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Nonlinear programming on generalized networks

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Evaluating two massively parallel machines

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NETGEN: A Program for Generating Large Scale Capacitated Assignment, Transportation, and Minimum Cost Flow Network Problems

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Nonlinear Network Programming on Vector Supercomputers: A Study on the CRAY X-MP

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OR Practice—Large-Scale Nonlinear Network Models and Their Application

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Stochastic Network Problems: Massively Parallel Solution

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Stochastic Network Problems: Massively Parallel Solution

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Parallel Algorithms for Network Problems

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Massively Parallel Solution of Large Scale Network Flow Problems

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Proximal minimizations with D-functions and the massively parallel solution of linear network programs

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A parallel descent algorithm for convex programming

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Data parallel computing for network-structured optimization problems

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Dual coordinate step methods for linear network flow problems

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Vectorization and multitasking of nonlinear network programming algorithms

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A comparative study of primal and dual approaches for solving separable and partially-separable nonlinear optimization problems

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Applying the progressive hedging algorithm to stochastic generalized networks

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A survey of dynamic network flows

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Solving multistage stochastic network programs on massively parallel computers

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An inertia-free filter line-search algorithm for large-scale nonlinear programming

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Some aspects of parallel and distributed iterative algorithms—A survey

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Data structures for network algorithms on massively parallel architectures

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Data-level parallel solution of min-cost network flow problems using ϵ-relaxations

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A comparison of Jacobi and Gauss-Seidel parallel iterations

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PARALLEL DECOMPOSITION OF MULTICOMMODITY FLOW PROBLEMS USING COERCION METHODS

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Synchronous and asynchronous implementations of relaxation algorithms for nonlinear network optimization

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Chapter 5 Parallel computing in network optimization

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Scalable parallel computations forlarge-scale stochastic programming

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A COMPARATIVE STUDY OF PARALLEL DECOMPOSITIONS FOR MULTICOMMODITY FLOW PROBLEMS∗

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Distributed asynchronous gradient algorithms for convex network flow problems

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Dual Ascent Methods for Problems with Strictly Convex Costs and Linear Constraints: A Unified Approach

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Partially Asynchronous, Parallel Algorithms for Network Flow and Other Problems

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Massively Parallel Row-Action Algorithms for Some Nonlinear Transportation Problems

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On the Fine-Grain Decomposition of Multicommodity Transportation Problems

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

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Convergence rate and termination of asynchronous iterative algorithms

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Massively Parallel Proximal Algorithms for Solving Linear Stochastic Network Programs

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Stochastic Network Programming for Financial Planning Problems

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Relaxation Methods for Problems with Strictly Convex Costs and Linear Constraints

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OR Practice—Large-Scale Nonlinear Network Models and Their Application

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A Massively Parallel Algorithm for Nonlinear Stochastic Network Problems

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A Decomposition Algorithm for the All-Pairs Shortest Path Problem on Massively Parallel Computer Architectures

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I Parallel Computation and Sensitivity Analysis in Nonlinear Optimization

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