M.S., Università degli Studi di Torino (Italy), 2007
B.S., Università degli Studi di Torino (Italy), 2004
Research Interests:
Applied probability
Stochastic modeling
Stochastic dynamic programming
Combinatorial optimization
Applications to management sciences and economics
Grants Funded:
National Science Foundation, CAREER Award, The effects of centralized and decentralized sequential decisions on system performance. (nsf)
National Science Foundation, Conference on probability theory and combinatorial optimization. (nsf)
Current Projects:
Sequential policies and the distributions of their total rewards in dynamic and stochastic knapsack problems,
joint with Y. T. Kuo and X. Xie.
Data-driven monitoring of the optimality of policies across many Markov decision problems,
joint with A. Belloni and X. Xie.
Working Papers:
Arlotto, A., Belloni, A. Fang, F. and Pekeč, S. (2024)
Ballot design and electoral cutcomes: the role of candidate order and party affiliation,
under review. (pdf)
Arlotto, A., Keskin, I. N., and Wei, Y. (2024) Online demand fulfillment problem with initial
inventory placement: a regret analysis, under review. (pdf)(SSRN)
Finalist in the 2024 POMS College of Supply Chain Management Best Student Paper Competition (Entrant: I. N. Keskin)
Published Papers:
Vera, A., Arlotto, A., Gurvich, I., and Levin, E. (2024) Dynamic resource allocation: the geometry and robustness of constant regret, Mathematics of Operations Research, forthcoming. (pdf)
Arlotto, A. and Xie, X. (2020) Logarithmic regret in the dynamic and stochastic knapsack problem with equal rewards, Stochastic Systems, 10, 170-191. (pdf)(arXiv)
Arlotto, A. and Gurvich, I. (2019) Uniformly bounded regret in the multi-secretary problem, Stochastic Systems, 9, 231-260. (pdf)(arXiv)
Winner of the 2021 INFORMS Applied Probability Society Best Publication Award
Arlotto, A., Frazelle, A. E., and Wei, Y. (2019) Strategic open routing in service networks, Management Science, 65, 735-750. (pdf)(online appendix)(ssrn)
Winner of the 2019 M&SOM Service Management SIG Best Paper Award
Finalist in the 2016 M&SOM Student Paper Competition (Entrant: A. E. Frazelle)
Arlotto, A. and Steele, J. M. (2018) A central limit theorem for costs in Bulinskaya's inventory management problem when deliveries face delays, Methodology and Computing in Applied Probability, 20, 839-854. (pdf)(arXiv)
Arlotto, A., Wei, Y., and Xie, X. (2018) An adaptive O(log n)-optimal policy for the online selection of a monotone subsequence from a random sample, Random Structures & Algorithms, 52, 41-53. (pdf)(arXiv)
Arlotto, A. and Steele, J. M. (2016) A central limit theorem for temporally non-homogenous Markov chains with applications to dynamic programming, Mathematics of Operations Research, 41, 1448-1468. (pdf)(arXiv)
Arlotto, A. and Steele, J. M. (2016) Beardwood-Halton-Hammersley theorem for stationary ergodic sequences: a counterexample, The Annals of Applied Probability, 26, 2141-2168. (pdf)(arXiv)
Arlotto, A., Mossel, E., and Steele, J. M. (2016) Quickest online selection of an increasing subsequence of specified size, Random Structures & Algorithms, 49, 235-252. (pdf)(arXiv)
Arlotto, A., Nguyen, V. V. , and Steele, J. M. (2015) Optimal online selection of a monotone subsequence: a central limit theorem, Stochastic Processes and their Applications, 125, 3596-3622. (pdf)(arXiv)
Arlotto, A., Gans, N., and Steele, J. M. (2014) Markov decision problems where means bound variances, Operations Research, 62, 864-875. (pdf)
Arlotto, A. and Steele, J. M. (2014) Optimal online selection of an alternating subsequence: a central limit theorem, Advances in Applied Probability, 46, 536-559. (pdf)(arXiv)
Arlotto, A., Chick, S. E., and Gans, N. (2014) Optimal hiring and retention policies for heterogeneous workers who learn, Management Science, 60, 110-129. (pdf)(online appendix)
Arlotto, A., Chen, R. W., Shepp, L. A. and Steele, J. M. (2011) Online selection of alternating subsequences from a random sample, Journal of Applied Probability, 48, 1114-1132.
(pdf)(arXiv)
Arlotto, A. and Steele, J. M. (2011) Optimal sequential selection of a unimodal subsequence of a random sequence, Combinatorics, Probability and Computing, 20, 799-814.
(pdf)(arXiv)
Arlotto, A. and Scarsini, M. (2009) Hessian orders and multinormal distributions, Journal of Multivariate Analysis, 100, 2324-2330.
(pdf)
Conference Proceedings:
Arlotto, A., Chick, S. E., and Gans, N. (2010) Optimal employee retention when inferring unknown learning curves, Proceedings of the 2010 Winter Simulation Conference, 1178-1188.
(pdf)
Alessandro Arlotto