OptMap: Using Dense Maps for Visualizing Multidimensional Optimization Problems

Mateus Espadoto, Mateus Espadoto, Francisco C. M. Rodrigues, Francisco C. M. Rodrigues, Nina S. T. Hirata, Alexandru C. Telea

2021

Abstract

Operations Research is a very important discipline in many industries, and although there were many developments since its inception, to our knowledge there are no visualization tools focused on helping users understand the decision variables’ domain space and its constraints for problems with more than two input dimensions. In this paper, we propose OptMap, a technique that enables the visual exploration of optimization problems using a two-dimensional dense map, regardless of the number of variables and constraints in the problem and for any kind of single-valued objective function. We show the technique in action for several optimization problems of different types, such as linear, nonlinear and integer, constrained and unconstrained problems.

Download


Paper Citation


in Harvard Style

Espadoto M., Rodrigues F., Hirata N. and Telea A. (2021). OptMap: Using Dense Maps for Visualizing Multidimensional Optimization Problems. In Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 3: IVAPP; ISBN 978-989-758-488-6, SciTePress, pages 123-132. DOI: 10.5220/0010288501230132


in Bibtex Style

@conference{ivapp21,
author={Mateus Espadoto and Francisco C. M. Rodrigues and Nina S. T. Hirata and Alexandru C. Telea},
title={OptMap: Using Dense Maps for Visualizing Multidimensional Optimization Problems},
booktitle={Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 3: IVAPP},
year={2021},
pages={123-132},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010288501230132},
isbn={978-989-758-488-6},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 3: IVAPP
TI - OptMap: Using Dense Maps for Visualizing Multidimensional Optimization Problems
SN - 978-989-758-488-6
AU - Espadoto M.
AU - Rodrigues F.
AU - Hirata N.
AU - Telea A.
PY - 2021
SP - 123
EP - 132
DO - 10.5220/0010288501230132
PB - SciTePress