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arXiv · 2412.04118

Extending Robinson Spaces: Complexity and Algorithmic Solutions for Non-Symmetric Dissimilarity Spaces

Francois Brucker·Pascal Préa·Christopher Thraves Caro
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Abstract

In this work, we extend the concept of Robinson spaces to asymmetric dissimilarities, enhancing their applicability in representing and analyzing complex data. Within this generalized framework, we introduce two different problems that extend the classical seriation problem: an optimization problem and a decision problem. We establish that these problems are NP-hard and NP-complete, respectively. Despite this complexity results, we identify several non-trivial instances where these problems can be solved in polynomial time, providing valuable insights into their tractability.

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Francois Brucker, Pascal Préa, Christopher Thraves Caro. 2024-12-05. Extending Robinson Spaces: Complexity and Algorithmic Solutions for Non-Symmetric Dissimilarity Spaces. https://arxiv.org/abs/2412.04118

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