System and method for dynamic pairing function optimization

A system for dynamic pairing function optimization, the system comprising:

• one or more processors;
• memory;
• one or more programs stored in the memory, the one or more programs comprising instructions for:
• receiving, at a server, a first filtered dataset corresponding to a plurality of orders for real-time deliveries of perishable goods from a plurality of merchants, wherein the first filtered dataset is filtered by a time threshold and a confirmation milestone;
• receiving, at the server, a second filtered dataset corresponding to a plurality of couriers, wherein the second filtered dataset is filtered by an active status threshold;
• generating a set of preferred data pairings from the first and second filtered datasets, wherein generating the set of preferred data pairings comprises:
• shard sorting the union of the first dataset and the second dataset into a plurality of sorted groups, wherein the shard sorting is based at least partially on geographic data associated data values in the first and second datasets;
• and
• for each sorted group:
• identifying possible data pairings between a first data value from the first dataset and a second data value from the second dataset;
• filtering the possible data pairings to eliminate infeasible pairings to form a set of feasible pairings, wherein infeasible pairings are determined using factors including transportation mode;
• generating possible routes associated with each feasible pairing;
• scoring each feasible pairing based on weighted factors;
• and
• solving, using a mathematical solver, for the set of feasible pairings that maximizes the sum of scores across all pairings;
• and
• offering the corresponding feasible pairing if a projected time value for a route is greater than or equal to an expected perishable good ready time value.

A non-transitory computer readable medium storing one or more programs configured for execution by a computer, the one or more programs comprising instructions for:

• receiving, at a server, a first filtered dataset corresponding to a plurality of orders created for real-time deliveries of perishable goods from a plurality of merchants, wherein the first filtered dataset is filtered by a time threshold and a confirmation milestone;
• receiving, at the server, a second filtered dataset corresponding to a plurality of available couriers, wherein the second filtered dataset is filtered by an active status threshold;
• generating a set of preferred data pairings from the first and second filtered datasets, wherein generating the set of preferred data pairings comprises:
• shard sorting the union of the first dataset and the second dataset into a plurality of sorted groups, wherein the shard sorting is based at least partially on geographic data associated data values in the first and second datasets;
• and
• for each sorted group:
• identifying possible data pairings between a first data value from the first dataset and a second data value from the second dataset;
• filtering the possible data pairings to eliminate infeasible pairings to form a set of feasible pairings, wherein infeasible pairings are determined using factors including transportation mode;
• generating possible routes associated with each feasible pairing;
• scoring each feasible pairing based on weighted factors;
• and
• solving, using a mathematical solver, for the set of feasible pairings that maximizes the sum of scores across all pairings;
• and
• offering the corresponding feasible pairing if a projected time value for a route is greater than or equal to an expected perishable good ready time value.