Publications of Alessandro Arlotto    :chronological  alphabetical  combined  bibtex listing:

Papers Published

1. Vera, A; Arlotto, A; Gurvich, I; Levin, E, Dynamic Resource Allocation: The Geometry and Robustness of Constant Regret, MATHEMATICS OF OPERATIONS RESEARCH, vol. 50 no. 4 (2025) [doi]
2. Arlotto, A; Keskin, IN; Wei, Y, Online Demand Fulfillment Problem with Initial Inventory Placement: A Regret Analysis (December, 2023)
3. Arlotto, A; Xie, X, Logarithmic regret in the dynamic and stochastic knapsack problem with equal rewards, Stochastic Systems, vol. 10 no. 2 (June, 2020), pp. 170-191 [doi]  [abs]
4. Arlotto, A; Gurvich, I, Uniformly Bounded Regret in the Multisecretary Problem, Stochastic Systems, vol. 9 no. 3 (September, 2019), pp. 231-260 [doi]  [abs]
5. Arlotto, A; Frazelle, AE; Wei, Y, Strategic open routing in service networks, Management Science, vol. 65 no. 2 (February, 2019), pp. 735-750, INFORMS [doi]  [abs]
6. Arlotto, A; Steele, JM, A Central Limit Theorem for Costs in Bulinskaya’s Inventory Management Problem When Deliveries Face Delays, Methodology and Computing in Applied Probability, vol. 20 no. 3 (September, 2018), pp. 839-854 [doi]  [abs]
7. Arlotto, A; Wei, Y; Xie, X, An adaptive O(log n)-optimal policy for the online selection of a monotone subsequence from a random sample, Random Structures and Algorithms, vol. 52 no. 1 (January, 2018), pp. 41-53, WILEY [doi]  [abs]
8. Arlotto, A; Michael Steele, J, A central limit theorem for temporally nonhomogenous markov chains with applications to dynamic programming, Mathematics of Operations Research, vol. 41 no. 4 (November, 2016), pp. 1448-1468, Institute for Operations Research and the Management Sciences (INFORMS) [doi]  [abs]
9. Arlotto, A; Mossel, E; Steele, JM, Quickest online selection of an increasing subsequence of specified size, Random Structures and Algorithms, vol. 49 no. 2 (September, 2016), pp. 235-252, WILEY [doi]  [abs]
10. Arlotto, A; Steele, JM, Beardwood-halton-hammersley theorem for stationary ergodic sequences: A counterexample, Annals of Applied Probability, vol. 26 no. 4 (August, 2016), pp. 2141-2168, Institute of Mathematical Statistics [doi]  [abs]
11. Arlotto, A; Nguyen, VV; Steele, JM, Optimal online selection of a monotone subsequence: A central limit theorem, Stochastic Processes and their Applications, vol. 125 no. 9 (August, 2014), pp. 3596-3622, Elsevier BV [doi]  [abs]
12. Arlotto, A; Gans, N; Steele, JM, Markov decision problems where means bound variances, Operations Research, vol. 62 no. 4 (January, 2014), pp. 864-875, Institute for Operations Research and the Management Sciences (INFORMS) [doi]  [abs]
13. Arlotto, A; Chick, SE; Gans, N, Optimal hiring and retention policies for heterogeneous workers who learn, Management Science, vol. 60 no. 1 (January, 2014), pp. 110-129, Institute for Operations Research and the Management Sciences (INFORMS) [doi]  [abs]
14. Arlotto, A; Steele, JM, Optimal online selection of an alternating subsequence: A central limit theorem, Advances in Applied Probability, vol. 46 no. 2 (January, 2014), pp. 536-559, Cambridge University Press (CUP) [doi]  [abs]
15. Arlotto, A; Chen, RW; Shepp, LA; Steele, JM, Online selection of alternating subsequences from a random sample, Journal of Applied Probability, vol. 48 no. 4 (December, 2011), pp. 1114-1132, Cambridge University Press (CUP) [doi]  [abs]
16. Arlotto, A; Steele, JM, Optimal sequential selection of a unimodal subsequence of a random sequence, Combinatorics Probability and Computing, vol. 20 no. 6 (November, 2011), pp. 799-814, Cambridge University Press (CUP) [doi]  [abs]
17. Arlotto, A; Gans, N; Chick, S, Optimal employee retention when inferring unknown learning curves, edited by Johansson, B; Jain, S; Montoya-Torres, J; Hugan, J; Yücesan, E, Proceedings Winter Simulation Conference (December, 2010), pp. 1178-1188, IEEE [doi]  [abs]
18. Arlotto, A; Scarsini, M, Hessian orders and multinormal distributions, Journal of Multivariate Analysis, vol. 100 no. 10 (November, 2009), pp. 2324-2330, Elsevier BV [doi]  [abs]