This webpage reports on my scientific production and is intended for my own use. In particular, 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, 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, entropy encoding, cross-entropy encoding, Kullback–Leibler divergence, tree metric, submodular functions, convexity, Schur convexity, phylogenetics, phylogenetic networks, mathematical modeling of tumor progression, genome-wide association studies, medical bioinformatics, deep reinforcement learning, clustering, optimization for machine learning.
Scopus author output analysis; ORCID: 0000-0001-9427-1562
Network design with applications on mathematics of evolution and computational phylogenetics
- D. Catanzaro, M. Frohn, O. Gascuel, and R. Pesenti. A Tutorial on the Balanced Minimum Evolution. European Journal of Operational Research, accepted on August 2021. Invited article.
- D. Catanzaro, M. Frohn, and R. Pesenti. An information theory perspective on the Balanced Minimum Evolution Problem. Operations Research Letters, 48(3): 362-367, 2020.
- D. Catanzaro, R. Pesenti, and L. Wolsey. On the Balanced Minimum Evolution Polytope. Discrete Optimization, 36, 1-33, 2020. (Tech Report: TR)
- D. Catanzaro and R. Pesenti. Enumerating Vertices of the Balanced Minimum Evolution Polytope. Computers and Operations Research, 109, 209-217, 2019.
- D. Catanzaro, S. E. Shackney, A. A. Schäffer, and R. Schwartz. Classifying the progression of Ductal Carcinoma from single-cell sampled data via integer linear programming: A case study. IEEE/ACM Transactions in Computational Biology and Bioinformatics, 13(4):643–655, 2016.
- D. Catanzaro, R. Aringhieri, M. Di Summa, and R. Pesenti. A branch-price-and-cut algorithm for the minimum evolution problem. European Journal of Operational Research, 244(3), 753–765, 2015. Typos. Unlabeled Phylogenies.
- D. Catanzaro, M. Labbé, and R. Pesenti. The balanced minimum evolution problem under uncertain data. Discrete Applied Mathematics, 161(13-14), 1789-1804, 2013.
- D. Catanzaro, R. Ravi, and R. Schwartz. A mixed integer linear programming model to reconstruct phylogenies from single nucleotide polymorphism fragments under the maximum parsimony criterion. BMC Algorithms for Molecular Biology, 8:3, 2013.
- D. Catanzaro, M. Labbé, R. Pesenti, and J. J. Salazar-González. The balanced minimum evolution problem. INFORMS Journal on Computing, 24(2), 276-294, 2012.
- R. Aringhieri, D. Catanzaro, and M. Di Summa. Optimal solutions for the balanced minimum evolution problem. Computers and Operations Research, 38(12), 1845–1854, 2011. Typos. Unlabeled Phylogenies.
- D. Catanzaro. Estimating phylogenies from molecular data. In Mathematical approaches to polymer sequence analysis and related problems, R. Bruni (Editor), Springer, New York, 149-176, 2010.
- D. Catanzaro. The minimum evolution problem: Overview and classification. Networks 53(2), 112-125, 2009.
- D. Catanzaro, M. Labbé, R. Pesenti, and J. J. Salazar-González. Mathematical models to reconstruct phylogenetic trees under the minimum evolution criterion. Networks 53(2), 126-140, 2009.
- D. Catanzaro, R. Pesenti, and M. C. Milinkovitch. An ant colony optimization algorithm for phylogenetic estimation under the minimum evolution principle. BMC Evolutionary Biology 7:228, 2007.
- L. Gatto, D. Catanzaro, and M. C. Milinkovitch. Assessing the applicability of the GTR model through simulations. Evolutionary Bioinformatics 2, 153-163, 2006.
- D. Catanzaro, R. Pesenti, and M. C. Milinkovitch. A non-linear optimization procedure to estimate distances and instantaneous substitution rate matrices under the GTR model. Bioinformatics 22(6), 708-715, 2006.
Coloring and covering with applications on haplotyping & disease association studies
- L. Porretta, D. Catanzaro, B. V. Halldórsson, and B. Fortz. A Branch&Price Algorithm for the Minimum Cost Clique Cover Problem in Max-Point Tolerance Graphs. 4OR, 17(1), 75-96, 2019.
- D. Catanzaro, M. Labbé, and B. V. Halldórsson. An integer programming formulation of the parsimonious loss of heterozygosity problem. IEEE/ACM Transactions in Computational Biology and Bioinformatics, 10(6), 1391-1402, 2013.
- D. Catanzaro, M. Labbé, and L. Porretta. A class representative model for pure parsimony haplotyping under uncertain data. PLoS One 6(3): e17937, 2011.
- D. Catanzaro, M. Andrien, M. Labbé, and M. Toungouz-Nevessignsky. Computer-aided human leukocyte antigen association studies: A case study for psoriasis and severe alopecia areata. Human Immunology 71(8), 783-788, 2010.
- D. Catanzaro, A. Godi, and M. Labbé. A class representative model for pure parsimony haplotyping. INFORMS Journal on Computing 22(2), 195–209, 2010.
- D. Catanzaro and M. Labbé. The pure parsimony haplotyping problem: Overview and computational advances. International Transactions in Operational Research 16(5), 561-584, 2009.
- 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
- D. Catanzaro, S. Coniglio, and F. Furini. On the exact separation of cover inequalities of maximum depth. Optimization Letters, 2021, to appear.
Telecommunications, manufacturing, scheduling, partitioning, and routing under uncertainty
- D. Catanzaro, R. Pesenti, R. Ronco. A new fast and accurate solution approach for the automatic scene detection problem. Computers and Operations Research, accepted 2021.
- D. Catanzaro, M. Labbé, and L. E. N. Gouveia. Improved integer linear programming formulations for the job sequencing and tool switching problem. European Journal of Operational Research, 244(3), 766–777, 2015.
- D. Catanzaro and C. Engelbeen. An integer linear programming formulation for the minimum cardinality segmentation problem. Algorithms, 8(4), 999-1020, 2015.
- D. Catanzaro, M. Labbé, and M. Salazar-Neumann. Reduction approaches for robust shortest path problems. Computers and Operations Research, 38(11), 1610-1619, 2011.
- D. Catanzaro, E. Gourdin, M. Labbé, and F. A. Özsoy. A branch-and-cut algorithm for the partitioning-hub location-routing problem. Computers and Operations Research 38(2), 539–549, 2011.
Articles submitted to international peer-review journals:
- H. Dehaybe, D. Catanzaro, and P. Chevalier. A Deep Reinforcement Learning approach for the Stochastic Inventory Problem. Operations Research, February 2021.
Feel free to contact me in the case instances of specific problems or source codes for any of the above works may be needed.