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A word cloud is a visual representation of the most frequently used words in a text or a set of texts. The words appear in different sizes, with the size of each word being proportional to its frequency of occurrence in the text. The more frequently a word is used, the larger it appears in the word cloud. This technique allows for a quick visualization of the most important themes and concepts in a text.
In the context of this page, the word cloud was generated from the publications of the author {}. The words in this cloud come from the titles, abstracts, and keywords of the author's articles and research papers. By analyzing this word cloud, you can get an overview of the most recurring and significant topics and research areas in the author's work.
The word cloud is a useful tool for identifying trends and main themes in a corpus of texts, thus facilitating the understanding and analysis of content in a visual and intuitive way.
Azevedo da Costa, L. C., Contardo, C., Desaulniers, G., & Pecin, D. (2021). Selective arc-ng pricing for vehicle routing. International Transactions in Operational Research, 28(5), 2633-2690. External link
Azevedo da Costa, L. C., Contardo, C., Desaulniers, G., & Pecin, D. G. (2020). Selective arc-ng pricing for vehicle routing. (Technical Report n° G-2020-07). External link
Aloise, D., & Contardo, C. (2018). A sampling-based exact algorithm for the solution of the minimax diameter clustering problem. Journal of Global Optimization, 71(3), 613-630. Available
Azevedo da Costa, L. C., Contardo, C., & Desaulniers, G. (2018). Exact branch-price-and-cut algorithms for vehicle routing. (Technical Report n° G-2018-41). External link
Contardo, C., Fukasawa, R., Rousseau, L.-M., & Vidal, T. (2024, May). Optimal Counterfactual Explanations for k-Nearest Neighbors Using Mathematical Optimization and Constraint Programming [Paper]. 8th International Symposium on Combinatorial Optimization (ISCO 2024), La Laguna, Tenerife, Spain. External link
Costa, L., Contardo, C., Desaulniers, G., & Yarkony, J. (2022). Stabilized Column Generation Via the Dynamic Separation of Aggregated Rows. INFORMS Journal on Computing, 34(2), 1141-1156. External link
Contardo, C., & Hertz, A. (2021). An exact algorithm for a class of geometric set-cover problems. Discrete Applied Mathematics, 300, 25-35. External link
Costa, L., Contardo, C., Desaulniers, G., & Yarkony, J. (2020). Stabilized column generation via the dynamic separation of aggregated rows. (Technical Report n° G-2020-36). External link
Contardo, C., & Hertz, A. (2020). An exact algorithm for a class of geometric set-cover problems. (Technical Report n° G-2020-17). External link
Costa, L., Contardo, C., & Desaulniers, G. (2019). Exact Branch-Price-and-Cut Algorithms for Vehicle Routing. Transportation Science, 53(4), 946-985. External link
Contardo, C., Desaulniers, G., & Lessard, F. (2015). Reaching the elementary lower bound in the vehicle routing problem with time windows. Networks, 65(1), 88-99. External link
Contardo, C., Morency, C., & Rousseau, L.-M. (2012). Balancing a dynamic public bike-sharing system. (Technical Report n° CIRRELT-2012-09). External link
Desaulniers, G., Pecin, D., & Contardo, C. (2019). Selective pricing in branch-price-and-cut algorithms for vehicle routing. EURO Journal on Transportation and Logistics, 8(2), 147-168. External link
Desaulniers, G., Pecin, D., & Contardo, C. (2016). Selective pricing in branch-price-and-cut algorithms for vehicle routing. (Technical Report n° G-2016-110). External link
Pecin, D., Contardo, C., Desaulniers, G., & Uchoa, E. (2017). New enhancements for the exact solution of the vehicle routing problem with time windows. INFORMS Journal on Computing, 29(3), 489-502. External link
Rastgar-Amini, F., Aloise, D., Contardo, C., & Desaulniers, G. (2024). Data Mining-Driven Shift Enumeration for Accelerating the Solution of Large-Scale Personnel Scheduling Problems. ACM Transactions on Evolutionary Learning and Optimization, 24 pages. External link
Rastgar-Amini, F., Aloise, D., Contardo, C., & Desaulniers, G. (2023). Data mining-driven shift enumeration for acceleratiing the solution of large-scale personnel scheduling problems. (Technical Report n° G-2023-61). External link
Rastgar Amini, F., Contardo, C., Desaulniers, G., & Gasse, M. (2022). Learning to enumerate shifts for large-scale flexible personnel scheduling problems. (Technical Report n° G-2022-29). External link
Rocha, D., Aloise, D., Aloise, D. J., & Contardo, C. (2022). Visual attractiveness in vehicle routing via bi-objective optimization. Computers & Operations Research, 137, 105507 (14 pages). Available
Rocha, D., Aloise, D., Aloise, D. J., & Contardo, C. (2020). Visual attractiveness in vehicle routing via bi-objective optimization. (Technical Report n° G-2020-65). External link
Rocha, D., Aloise, D., Aloise, D. J., & Contardo, C. (2017). A bi-objective vehicle routing problem integrating routing operations into tactical clustering decisions. (Technical Report n° G-2017-30). External link
Ton, K. T., Aloise, D., & Contardo, C. (2024). On Removing Diverse Data for Training Machine Learning Models. In Rassias, T. M., & Pardalos, P. M. (eds.), Mathematical Analysis, Differential Equations and Applications (Vol. 11, pp. 761-783). External link
Ton, K., Aloise, D., & Contardo, C. (2022). On removing diverse data for training machine learning models. (Technical Report n° G-2022-38). External link