On Mathematical Optimization for the visualization of frequencies and adjacencies as rectangular maps

In this paper, we address the problem of visualizing a frequency distribution and an adjacency relation attached to a set of individuals. We represent this information using a rectangular map, i.e., a subdivision of a rectangle into rectangular portions so that each portion is associated with one in...

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Bibliographic Details
Authors: Carrizosa Priego, Emilio José, Guerrero Lozano, Vanesa, Romero Morales, María Dolores
Format: article
Status:Published version
Publication Date:2018
Country:España
Institution:Universidad de Sevilla (US)
Repository:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/107811
Online Access:https://hdl.handle.net/11441/107811
https://doi.org/10.1016/j.ejor.2017.07.023
Access Level:Open access
Keyword:Mixed Integer Linear Programming
Visualization
Multidimensional Scaling
Rectangular maps
Frequencies and adjacencies
Description
Summary:In this paper, we address the problem of visualizing a frequency distribution and an adjacency relation attached to a set of individuals. We represent this information using a rectangular map, i.e., a subdivision of a rectangle into rectangular portions so that each portion is associated with one individual, their areas reflect the frequencies, and the adjacencies between portions represent the adjacencies between the individuals. Due to the impossibility of satisfying both area and adjacency requirements, our aim is to fit as well as possible the areas, while representing as many adjacent individuals as adjacent rectangular portions as possible and adding as few false adjacencies, i.e., adjacencies between rectangular portions corresponding to non-adjacent individuals, as possible. We formulate this visualization problem as a Mixed Integer Linear Programming (MILP) model. We propose a matheuristic that has this MILP model at its heart. Our experimental results demonstrate that our matheuristic provides rectangular maps with a good fit in both the frequency distribution and the adjacency relation.