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everest.jl's Introduction

About Everest

This project is work in progress.

Everest is an interior point optimization solver for problems of the form:

min f(x)

Ax = b

x >= 0

Where f(x) is any smooth non-convex function.

How to install

  1. Install the linear solver MUMPS.jl. Currently this package is only supported in Linux or Mac OS X. If you want to add an new linear solver you can do so in this directory.

  2. Run the following code in julia:

Pkg.add("JuMP")
Pkg.add("MAT")
Pkg.clone("https://github.com/ohinder/advanced_timer.jl.git")
Pkg.clone("https://github.com/ohinder/Everest.jl.git")

  1. Install CUTEst by following the instructions in CUTEst.jl

  2. To test your installation run in julia:

using Everest
Pkg.test("Everest")

How to use

to do ...

everest.jl's People

Contributors

ohinder avatar

Watchers

James Cloos avatar avatar

everest.jl's Issues

heuristics

  • change mumps parameters
  • increase delta when step size is small
  • s-heuristic
  • second order corrections

better initial delta strategy

use golden search on log scale (get delta within factor of 10).

set initial bounds for delta based on diagonals (i.e. diagonals must be positive, diagonal dominance is sufficient)

pick diagonals s.t. matrix diagonally dominant or at least only select hessian with non-zeros

central path(s)

-show that a path must begin and end at a singular point of the hessian.

package tests

add some tests to check packages are working correctly

jtest

use JuMP to easily create non-linear programming test problems

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