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Costa, L. R., Aloise, D., Gianoli, L. G., & Lodi, A. (2022). Heuristics for optimizing 3D mapping missions over swarm-powered ad-hoc clouds. Journal of Heuristics, 28(4), 539-582. Lien externe
Costa, L. R., Aloise, D., Gianoli, L. G., & Lodi, A. (mai 2022). OptiMaP: swarm-powered Optimized 3D Mapping Pipeline for emergency response operations [Communication écrite]. 18th International Conference on Distributed Computing in Sensor Systems (DCOSS 2022), Marina del Rey, Los Angeles, CA, USA. Lien externe
Lodi, A., Olivier, P., Pesant, G., & Sankaranarayanan, S. (2022). Fairness over time in dynamic resource allocation with an application in healthcare. Mathematical Programming, 34 pages. Lien externe
Accorsi, L., Lodi, A., & Vigo, D. (2022). Guidelines for the computational testing of machine learning approaches to vehicle routing problems. Operations Research Letters, 50(2), 229-234. Lien externe
Bonami, P., Lodi, A., & Zarpellon, G. (2022). A classifier to decide on the linearization of mixed-integer quadratic problems in CPLEX. Operations Research, 70(6), 3303-3320. Lien externe
Carvalho, M., Lodi, A., & Pedroso, J. P. (2022). Computing equilibria for integer programming games. European Journal of Operational Research, 303(3), 1057-1070. Lien externe
Costa, L. R., Aloise, D., Gianoli, L. G., & Lodi, A. (2022). Heuristics for optimizing 3D mapping missions over swarm-powered ad-hoc clouds. Journal of Heuristics, 28(4), 539-582. Lien externe
Costa, L. R., Aloise, D., Gianoli, L. G., & Lodi, A. (mai 2022). OptiMaP: swarm-powered Optimized 3D Mapping Pipeline for emergency response operations [Communication écrite]. 18th International Conference on Distributed Computing in Sensor Systems (DCOSS 2022), Marina del Rey, Los Angeles, CA, USA. Lien externe
Dey, S. S., Kazachkov, A., Lodi, A., & Munoz, G. (2022). Cutting plane generation through sparse principal component analysis. SIAM Journal on Optimization, 32(2), 1319-1343. Lien externe
Gotlieb, N., Azhie, A., Sharma, D., Spann, A., Suo, N.-J., Tran, J., Orchanian-Cheff, A., Wang, B., Goldenberg, A., Chassé, M., Cardinal, H., Cohen, J. P., Lodi, A., Dieude, M., & Bhat, M. (2022). The promise of machine learning applications in solid organ transplantation. npj Digital Medicine, 5(1), 13 pages. Lien externe
Jalbert, J., Cardinal, H., Lodi, A., Weller, J.-N., & Tocco, H.-M. (juin 2022). Predicting Waiting Time and Quality of Kidney Offers for Kidney Transplant Candidates [Communication écrite]. 20th International Conference on Artificial Intelligence in Medicine (AIME 2022), Halifax, NS, Canada. Lien externe
Jena, S. D., Lodi, A., & Sole, C. (2022). On the Estimation of Discrete Choice Models to Capture Irrational Customer Behaviors. INFORMS Journal on Computing, 34(3), 1606-1625. Lien externe
Khalil, E. B., Morris, C., & Lodi, A. (février 2022). MIP-GNN: A Data-Driven Framework for Guiding Combinatorial Solvers [Communication écrite]. 36th AAAI Conference on Artificial Intelligence (AAAI 2022). Publié dans Proceedings of the ... AAAI Conference on Artificial Intelligence, 36(9). Lien externe
Labassi, A. G., Chetelat, D., & Lodi, A. (novembre 2022). Learning to Compare Nodes in Branch and Bound with Graph Neural Networks [Affiche]. 36th Conference on Neural Information Processing Systems (NeurIPS 2022), New Orleans, LA, USA. Lien externe
Labassi, A. G., Chetelat, D., & Lodi, A. (novembre 2022). Learning to Compare Nodes in Branch and Bound with Graph Neural Networks [Communication écrite]. 36th Conference on Neural Information Processing Systems (NeurIPS 2022), New Orleans, LA, USA. Lien externe
Labassi, A. G., Chetelat, D., & Lodi, A. (novembre 2022). Learning to Compare Nodes in Branch and Bound with Graph Neural Networks [Présentation]. Dans 36th Conference on Neural Information Processing Systems (NeurIPS 2022), New Orleans, LA, USA. Lien externe
Liu, D., Fischetti, M., & Lodi, A. (février 2022). Learning to Search in Local Branching [Communication écrite]. 36th AAAI Conference on Artificial Intelligence (AAAI 2022). Publié dans Proceedings of the ... AAAI Conference on Artificial Intelligence, 36(4). Lien externe
Lodi, A., Olivier, P., Pesant, G., & Sankaranarayanan, S. (2022). Fairness over time in dynamic resource allocation with an application in healthcare. Mathematical Programming, 34 pages. Lien externe
Lodi, A., Tanneau, M., & Vielma, J. P. (2022). Disjunctive cuts in mixed-integer conic optimization. Mathematical Programming, 199(1-2), 671-719. Lien externe
Müller, B., Muñoz, G., Gasse, M., Gleixner, A., Lodi, A., & Serrano, F. (2022). On generalized surrogate duality in mixed-integer nonlinear programming. Mathematical Programming, 2021(1-2), 1-30. Disponible
Niroumandrad, N., Lahrichi, N., & Lodi, A. (2022). Learning tabu search algorithms : a scheduling application. (Rapport technique). Lien externe
Ricard, L., Desaulniers, G., Lodi, A., & Rousseau, L.-M. (2022). Increasing schedule reliability in the multi-depot vehicle scheduling problem with stochastic travel time. (Rapport technique n° 2022-30). Lien externe
Ricard, L., Desaulniers, G., Lodi, A., & Rousseau, L.-M. (2022). Predicting the probability distribution of bus travel time to measure the reliability of public transport services. Transportation Research Part C-Emerging Technologies, 138, 103619 (16 pages). Lien externe
Rostami, B., Chitsaz, M., Arslan, O., Laporte, G., & Lodi, A. (2022). Single Allocation Hub Location with Heterogeneous Economies of Scale. Operations Research, 70(2), 766-785. Lien externe
Rostami, B., Errico, F., & Lodi, A. (2022). A convex reformulation and an outer approximation for a large class of binary quadratic programs. Operations Research, 71(2), 471-486. Lien externe
Scavuzzo, L., Chetelat, D., Lodi, A., Chen, F. Y., Gasse, M., Yorke-Smith, N., & Aardal, K. (novembre 2022). Learning to Branch with Tree MDPs [Affiche]. 36th Conference on Neural Information Processing Systems (NeurIPS 2022), New Orleans, LA, USA. Lien externe
Scavuzzo, L., Chetelat, D., Lodi, A., Chen, F. Y., Gasse, M., Yorke-Smith, N., & Aardal, K. (novembre 2022). Learning to Branch with Tree MDPs [Présentation]. Dans 36th Conference on Neural Information Processing Systems (NeurIPS 2022), New Orleans, LA, USA. Lien externe
