Daniele Catanzaro

Scientific Production

This webpage reports on my scientific production and is intended for my own use.

The works listed below are classified by application areas and concern exclusively manuscripts submitted to or published in international peer-review scientific journals. Some of the linked files may be covered by publisher copyrights. If you reached this page, please ensure that your institution has the appropriate subscription before accessing any of the PDFs below.

Keywords: combinatorial optimization, integer programming, polyhedral combinatorics, decomposition algorithms, branch-&-cut, branch-price-&-cut, computational complexity, routing, network design, coloring, covering, partitioning, location, games on graphs, constructive characterizations, high performance computing, massive parallel enumeration, enumeration of trees, lattices of unrooted binary trees, tree imbalance, tree coding, Huffman coding, information entropy, entropy encoding, cross-entropy encoding, Kullback–Leibler divergence, encryption schemes, tree metric, submodular functions, convexity, Schur convexity, phylogenetics, phylogenetic networks, mathematical modeling of tumor progression, genome-wide association studies, medical bioinformatics, deep reinforcement learning, hierarchical clustering, optimization aspects of machine learning.


Research Projects and related supervision activities

Classification of the scientific production by topics

Network design with applications to mathematics of evolution and computational phylogenetics

Coloring and covering with applications to haplotyping & disease association studies

Graph theory

  • D. Catanzaro, S. Chaplick, S. Felsner, B. V. Halldórsson, M. M. Halldórsson, T. Hixon, and J. Stacho. Max point-tolerance graphs. Discrete Applied Mathematics, 216(1): 84-97, 2017.  

Cutting plane methods

Telecommunications, manufacturing, scheduling, partitioning, and routing under uncertainty

Articles submitted to international peer-review journals:

  • D. Catanzaro, R. Pesenti, A. Sapucaia, and L. Wolsey. Optimizing over path-length matrices of unrooted binary trees. Submitted to Mathematical Programming, 2023.
  • H. Dehaybe, D. Catanzaro, and P. Chevalier. Continuous deep reinforcement learning for non-stationary stochastic inventory optimization. Submitted to the European Journal of Operational Research, 2022.
  • A. Gasparin, and F. J. C. Verdù, D. Catanzaro, and L. Castelli. An evolution strategy approach for the balanced minimum evolution problem. Submitted to Bioinformatics, 2023.

Articles in preparation:

  • D. Catanzaro and A. Sapucaia. A matheuristic for the Balanced Minimum Evolution Problem, 2023.
  • D. Catanzaro and R. Pesenti. On numerical instabilities of Balanced Minimum Evolution Problem, 2023.

Other Publications (Book Chapters, Conference Proceedings, Invited Talks…)

Feel free to contact me in the case instances of specific problems or source codes for any of the above works may be needed.