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Daniel Aloise
M.Sc. (PUC-Rio, Brésil) et un Ph.D. (Poly)

Research interests and affiliations

Research interests

• Data Science • Big Data • Optimization • Mathematical Programming

Expertise type(s) (NSERC subjects)
  • 1601 Operations research and management science
  • 2510 Adaptive, learning and evolutionary systems
  • 2713 Algorithms
  • 2715 Optimization


Recent publications
Conference paper
Aloise, D. & Contardo, C. (2018). A sampling-based exact algorithm for the solution of the minimax diameter clustering problem. Paper presented at the 13th Global Optimization Workshop (GOW 2016), Braga, Portugal. (Published in Journal of Global Optimization, 71(3), 613-630). Retrieved from
Journal article
Da Silva, T.G., De Sousa Filho, G.F., Barbosa, I.A.M., Mladenovic, N., Cabral, L.A.F., Ochi, L.S. & Aloise, D. (2018). Efficient heuristics for the minimum labeling global cut problem. Electronic Notes in Discrete Mathematics, 66, 23-30. Retrieved from
Journal article
Gonçalves-e-Silva, K., Aloise, D. & Xavier-de-Souza, S. (2018). Parallel synchronous and asynchronous coupled simulated annealing. Journal of Supercomputing, 74(6), 2841-2869. Retrieved from
Book chapter
Pereira, T., Aloise, D., Brimberg, J. & Mladenović, N. (2018). Review of Basic Local Searches for Solving the Minimum Sum-of-Squares Clustering Problem. In P.M. Pardalos & A. Migdalas (Eds.), Open Problems in Optimization and Data Analysis (Vol. 141, pp. 249-270). Cham: Springer. Retrieved from

Supervision at Polytechnique


  • Master's Thesis (1)

    • Hulot, P. (2018). Towards Station-Level Demand Prediction for Effective Rebalancing in Bike-Sharing Systems (Master's Thesis, École Polytechnique de Montréal). Retrieved from