Amazon Technologies, Inc.

Bhargav Kunkulagunta

Julian Enrique Pachon

Marc Joseph Anderson

Rohit Malshe

Dipal Patel Gupta

Nader M Kabbani

Daniel Esteban Merchan

Karthik Charan Konduri

Jatin Arora

Techniques for dividing a geographical area into districts are described herein. Geospatial vector data, barrier geospatial vector data, road infrastructure data, and historical delivery demand data for a geographical area may be obtained. A plurality of clusters from a stratified sampling of data points for the delivery demand data and barrier penalties from a barrier-aware road graph are generated. A first set of polygons for the plurality of clusters may be generated using a concave hull algorithm. A second set of polygons may be generated using a barrier constrained network Voronoi algorithm that uses the barrier-aware road graph and the first set of polygons as seeds. The second set of polygons may be modified using a bounded Voronoi algorithm that uses a raster cost allocation based on barrier penalties. Coordinates for each polygon of the modified second set of polygons are determined that divide the geographical area.

Systems and methods for road network aware geographical unit generation

Described are systems and methods directed to determining a topology for the efficient allocation and distribution of a service to customers that are distributed over a geographic area. For example, the topology can facilitate the planning, scheduling, and allocation of resources for the efficient provisioning of services to customers at locations distributed over the geographic area. Certain input parameters and/or constraints associated with the provisioning of the service may be processed to define a cost function that may represent a total cost of providing the service while ensuring that none of the constraints are exceeded. The cost function may be optimized to determine a lowest relative cost for providing the services to the customers using the various mechanisms and/or types of resources, and a topology associated with the optimized cost function can be generated to specify how the service should be provided to satisfy the demand.

Determining a topology for distribution of services using demand aggregation

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Hyderabad, India

Bhargav Kunkulagunta