Skip to content
lfprudentePublic

About

No description, website, or topics provided.

Resources

Stars

1 star

Watchers

2 watching

Forks

Repository files navigation

A Proximal Gradient Method with an Explicit Linesearch for Multiobjective Optimization

This repository contains the source codes for the numerical experiments described in the article:

Y. Bello-Cruz, J.G. Melo, L.F. Prudente, and R.V.G. Serra,
A Proximal Gradient Method with an Explicit Linesearch for Multiobjective Optimization, technical report, 2024.

Date: November 2024


Contents

The repository includes the following routines:

Main Routine

  • main.m
    Controls the execution of the experiments, allowing users to:
    • Select the problem to be solved.
    • Choose the optimization algorithm to apply.

Algorithms

  • ProxGrad.m
    Contains implementations of:

    • Explicit-MPG: Explicit Multiobjective Proximal Gradient algorithm.
    • Armijo-MPG: Multiobjective Proximal Gradient with Armijo line search.
    • Implicit-MPG: Implicit Multiobjective Proximal Gradient algorithm.
  • ProxGradAcc.m
    Contains implementations of:

    • Accelerated-MPG: Accelerated Multiobjective Proximal Gradient algorithm.
    • Normal-MPG: Normal Proximal Gradient algorithm.

Auxiliary Routines

  • inip.m
    Defines the initial parameters for the optimization problems.

  • evalg.m
    Implements the functions G_j.

  • evalgradg.m
    Computes the gradient of the functions G_j.

  • evalh.m
    Implements the functions H_j.

  • datas.m
    Generates the data for the functions H_j.

  • subproblemProxGrad.m
    Solves the subproblem required in the proximal gradient methods.

Line Search Routines

  • explicitLS.m
    Implements the explicit line search used in Explicit-MPG.

  • explicitLSone.m
    Handles the line search for a single objective function in Explicit-MPG.

  • armijo.m
    Implements the Armijo line search used in Armijo-MPG.

  • implicitLS.m
    Implements the implicit line search used in Implicit-MPG.


Instructions

To run the numerical experiments:

  1. Open the file main.m.
  2. Select the desired problem and algorithm in the code.
  3. Run the script and view the results on the screen.

License

This project is licensed under the GNU General Public License (GPL) version 3. For more information, see the LICENSE file.

About

No description, website, or topics provided.

Resources

Stars

1 star

Watchers

2 watching

Forks

Releases

Packages

Contributors

Languages