On the Characterization of Classes of Floorplans by Pattern-Avoiding Permutation Matrices

Let R be an axis-aligned rectangle. We define a floorplan as a partition of R into rectangular regions (rooms) such that each vertex is shared by at most three rooms. Following the approach of Nakano et al.,we also assume the presence of a set of points that impose constraints on the walls passing through them, allowing only horizontal or vertical segments. These constraints can be encoded by a permutation matrix whose entries are labeled H and V, which we refer to as a pattern matrix. In this work, we characterize the well-known classes of guillotine, diagonal, and diagonal–guillotine floorplans in terms of the presence of specific families of pattern matrices. In this way, we translate a purely geometric characterization into a combinatorial one.

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Journal
Mathematics
Published
2026-01-15
DOI
https://doi.org/10.3390/math14020310
Primary Topic
Digital Image Processing Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

On the Characterization of Classes of Floorplans by Pattern-Avoiding Permutation Matrices

Elisa Pergola, Andrea Frosini, Simone Rinaldi
Mathematics
Digital Image Processing Techniques
article

On the Characterization of Classes of Floorplans by Pattern-Avoiding Permutation Matrices

Elisa Pergola, Andrea Frosini, Simone Rinaldi
article en

Abstract

Let R be an axis-aligned rectangle. We define a floorplan as a partition of R into rectangular regions (rooms) such that each vertex is shared by at most three rooms. Following the approach of Nakano et al.,we also assume the presence of a set of points that impose constraints on the walls passing through them, allowing only horizontal or vertical segments. These constraints can be encoded by a permutation matrix whose entries are labeled H and V, which we refer to as a pattern matrix. In this work, we characterize the well-known classes of guillotine, diagonal, and diagonal–guillotine floorplans in terms of the presence of specific families of pattern matrices. In this way, we translate a purely geometric characterization into a combinatorial one.

MathematicsVol. 14(2)
University of Siena (IT), University of Florence (IT)
Gruppo Nazionale per il Calcolo Scientifico
Sustainable cities and communities
Openalex Percentile: Top 88%
Digital Image Processing Techniques
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On the Characterization of Classes of Floorplans by Pattern-Avoiding Permutation Matrices — Elisa Pergola, Andrea Frosini, et al. · Mathematics (2026) | TGRS Research Map | TGRS