Modeling of optimal routes for distributed cargo deliveries

The considered cargo delivery scheme uses the principles of parallel computing in supercomputers and distributed data processing in network structures. However, if in information technology these principles lead to the achievement of high performance when solving volumetric simulation and modeling tasks, then in the organization of distributed or parallel cargo deliveries, the goal is to minimize costs. The main thing in the scheme is the principle of parallelization of routes using several shipping carriers simultaneously, and these auxiliary shipping carriers can be based on the main shipping forwarder. An example of such a delivery system can be a van transporting several autonomous carriers, which, in turn, can carry out simultaneous (parallel) deliveries. Delivery routes are determined based on customer coordinates, selection of acceptable starting points for auxiliary shipping carriers, technical and energy limitations of the main and auxiliary shipping carriers, as well as minimizing the amount of time spent on delivery operations. The constructed algorithm for solving the problem of routing parallel deliveries using primary and secondary carriers reduces the time and resources of delivery. The algorithm is implemented in Python using libraries for processing and visualizing trajectories and other spatiotemporal data, packages for extracting, modeling, analyzing and visualizing street networks.