| Multi-site household waste generation forecasting using a deep learning approach M Cubillos Waste Management 115, 8-14, 2020 | 68 | 2020 |
| A bi-objective k-nearest-neighbors-based imputation method for multilevel data M Cubillos, S Wøhlk, JN Wulff Expert Systems with Applications 204, 117298, 2022 | 23 | 2022 |
| A multilevel Bayesian framework for predicting municipal waste generation rates M Cubillos, JN Wulff, S Wøhlk Waste Management 127, 90-100, 2021 | 19 | 2021 |
| Solution of the maximal covering tour problem for locating recycling drop-off stations M Cubillos, S Wøhlk Journal of the Operational Research Society 72 (8), 1898-1913, 2021 | 15 | 2021 |
| A real options approach for joint overhaul and replacement strategies with mean reverting prices A Mac Cawley, M Cubillos, R Pascual Annals of Operations Research 286, 303-324, 2020 | 11 | 2020 |
| An enhanced path planner for electric vehicles considering user-defined time windows and preferences M Cubillos, M Dell’Amico, O Jabali, F Malucelli, E Tresoldi Energies 16 (10), 4173, 2023 | 2 | 2023 |
| On the effect of using sensors and dynamic forecasts in inventory-routing problems M Cubillos, R Spliet, S Wøhlk INFOR: Information Systems and Operational Research 60 (4), 473-490, 2022 | 2 | 2022 |
| biokNN: A bi-objective imputation method for multilevel data in R M Cubillos | 2 | 2021 |
| An Enhanced Path Planner for Electric Vehicles Considering User-Defined Time Windows and Preferences. Energies 2023, 16, 4173 M Cubillos, M Dell’Amico, O Jabali, F Malucelli, E Tresoldi | | 2023 |
| Optimization and data analytics in waste management ME Cubillos Aarhus Universitet, 2022 | | 2022 |
Sanne WøhlkProfessor in Operations Research, Aarhus UniversityVerified email at econ.au.dk
