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A Matlab implementation of a revisited version of the MINRES for solving sparse and big linear systems arising from the KKT system of a quadratic MCF problem

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Computational Mathematics for Learning and Data Analysis

Getting Started

The following repository contains the non ML project 27 of the CM course.

Prerequisites

Given N the number of nodes and E the number of edges of the graph, the instances we use come from a .txt file and have the following structure: the first N rows are formatted like that: 'n' | node | supply, while the rows from the (N+1)-th to the last (E+N) have this format: 'a' | source_node | destinatation_node | cost.

Execution

The main function is main(filename, mode, generate, distribution) where:

  • filename is the path of the file containing the instance;
  • mode is the execution mode ('residual', 'rate', 'minres', 'precond');
  • generate is a boolean variable which indicates if the function has to generate or to load the vector D;
  • distribution is the probability distribution of data in the vector D choosen between 7 fixed distributions.

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A Matlab implementation of a revisited version of the MINRES for solving sparse and big linear systems arising from the KKT system of a quadratic MCF problem

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