Abstract: A system described herein may efficiently perform a multi-destination backward search, which may be a part of performing a bidirectional search in a node map that implements contraction hierarchy techniques. Lowest cost paths to each node reachable to each destination node of a set of destination nodes may be computed. A queue may be initialized with the set of destination nodes. For each particular node in the queue, the system may add higher priority neighbors of the particular node to the queue, identify costs of outgoing links from the particular node to the higher priority neighbors, compute lowest cost paths associated with the set of destination nodes based on the identified costs of outgoing links from the particular node to the higher priority neighbors and any previously computed lowest cost paths associated with the set of destination nodes, and increment to a next node in the queue.

Abstract: A vehicle routing platform may store, in a first data structure, a value at a logical index for each pair of locations of a plurality of pairs of locations. The logical index, for a pair of locations, indicates whether a travel time has been determined. The vehicle routing platform may store, in a second data structure, an offset index for each predetermined logical index of one or more predetermined logical indexes of the first data structure. The offset index, for a predetermined logical index, may be based on a quantity of logical indexes preceding the predetermined logical index in the first data structure. The vehicle routing platform may store, in a third data structure, travel times between pairs of locations of a portion of the plurality of pairs of locations. The vehicle routing platform may determine a travel time, between a pair of locations, using the data structures.

Abstract: One or more computing devices, systems, and/or methods for constructing and utilizing a search structure for identifying tasks to assign to entities are provided. The search structure is constructed to partition tasks and represent time constraints for performing the tasks and distance constraints corresponding to locations of the tasks. A search of the search structure is performed to identify a set of nearest tasks with respect to a target task. Tasks within the set of nearest tasks may be assigned to an entity to perform.