Bernardo Pagnoncelli
Bernardo Pagnoncelli
Associate Professor, SKEMA Business School
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Sample average approximation method for chance constrained programming: theory and applications
BK Pagnoncelli, S Ahmed, A Shapiro
Journal of optimization theory and applications 142 (2), 399-416, 2009
Risk aversion in multistage stochastic programming: A modeling and algorithmic perspective
T Homem-de-Mello, BK Pagnoncelli
European Journal of Operational Research 249 (1), 188-199, 2016
Chance-constrained problems and rare events: an importance sampling approach
J Barrera, T Homem-de-Mello, E Moreno, BK Pagnoncelli, G Canessa
Mathematical Programming 157, 153-189, 2016
Scenario reduction for stochastic programs with conditional value-at-risk
S Arpón, T Homem-de-Mello, B Pagnoncelli
Mathematical Programming 170 (1), 327-356, 2018
Risk-return trade-off with the scenario approach in practice: a case study in portfolio selection
BK Pagnoncelli, D Reich, MC Campi
Journal of Optimization Theory and Applications 155, 707-722, 2012
Underground mine scheduling under uncertainty
P Nesbitt, LR Blake, P Lamas, M Goycoolea, BK Pagnoncelli, A Newman, ...
European Journal of Operational Research 294 (1), 340-352, 2021
The optimal harvesting problem under price uncertainty
A Piazza, BK Pagnoncelli
Annals of Operations Research, 2014
Partially observable multistage stochastic programming
O Dowson, DP Morton, BK Pagnoncelli
Operations Research Letters 48 (4), 505-512, 2020
A risk averse approach to the capacity allocation problem in the airline cargo industry
M Wada, F Delgado, BK Pagnoncelli
Journal of the Operational Research Society 68, 643-651, 2017
A multistage stochastic programming model for the network air cargo allocation under capacity uncertainty
F Delgado, R Trincado, BK Pagnoncelli
Transportation Research Part E: Logistics and Transportation Review 131, 292-307, 2019
Better management of production incidents in mining using multistage stochastic optimization
L Reus, B Pagnoncelli, M Armstrong
Resources Policy 63, 101404, 2019
Can asset allocation limits determine portfolio risk–return profiles in DC pension schemes?
T Gutierrez, B Pagnoncelli, D Valladão, A Cifuentes
Insurance: Mathematics and Economics 86, 134-144, 2019
Incorporating convex risk measures into multistage stochastic programming algorithms
BK Dowson, O., Morton, D. and Pagnoncelli
Annals of Operations Research, 2022
Designing coalition-based fair and stable pricing mechanisms under private information on consumers’ reservation prices
H Le Cadre, B Pagnoncelli, T Homem-De-Mello, O Beaude
European Journal of Operational Research 272 (1), 270-291, 2019
The optimal harvesting problem under price uncertainty: the risk averse case
BK Pagnoncelli, A Piazza
Annals of Operations Research 258, 479-502, 2017
Uma Introduçaoa Otimizaçao sob Incerteza
HJ Bortolossi, BK Pagnoncelli
III Bienal da Sociedade Brasileira de Matemática, 2006
The risk-averse ultimate pit problem
G Canessa, E Moreno, BK Pagnoncelli
Optimization and Engineering 22, 2655-2678, 2021
Pension Funds in Mexico and Chile: A Risk-Reward Comparison
H Schlechter, B Pagnoncelli, A Cifuentes
Available at SSRN 3359920, 2019
A synthetic data-plus-features driven approach for portfolio optimization
BK Pagnoncelli, D Ramírez, H Rahimian, A Cifuentes
Computational Economics 62 (1), 187-204, 2023
An ADMM algorithm for two-stage stochastic programming problems
S Arpón, T Homem-de-Mello, BK Pagnoncelli
Annals of Operations Research 286 (1), 559-582, 2020
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