The problems addressed in this project required the use of Mathematical Optimization tools for their modeling and subsequent resolution. Specifically, various Mathematical Programming formulations were developed to model these problems, analyzed from the perspective of linear and nonlinear Integer Programming.
To solve them, we developed efficient exact algorithms using both decomposition techniques and smart enumeration methods. For large-scale problems, heuristic and Matheuristic algorithms were proposed, incorporating Machine Learning techniques to handle large volumes of data.
You can manage and share content related to the specific work being carried out across all devices and the cloud, ensuring file traceability and process security at all times.
A significant reduction in time
when assigning loads, achieved through allocation algorithms specifically developed for this purpose.
The ability to calculate ETA
using modeled processes and future time projections.
Integration of various traffic models
by applying specific control criteria for each one.
Real-time insight into the status of your traffic.
Access to data on emission reductions.
Economic growth
driven by optimization through the developed algorithms, focusing on assigning the best option, calculated in real time based on the actual situation of the fleet.
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