The system is deployed progressively — lower-resolution grids and lower destination counts are built first. Dynamic programming and partial path reuse mean shared sub-routes are stored once and referenced many times. Modern storage costs continue to decline rapidly, and the system runs on distributed storage architectures. The storage cost is a one-time capital expenditure for permanent, reusable solutions — compared to the aggregate CPU cost of recomputing the same routes billions of times, the investment is economically trivial.
Every real-world coordinate is mapped to its nearest canonical grid point through the Coordinate Mapper module. This introduces a small positional error — the "snap distance" — equal to at most half the spacing between grid points. At high resolutions (1,000x1,000 or above), the snap distance is operationally negligible. Resolution improves automatically as the system matures.
Yes — within the constraint of the grid. The precomputation engine exhaustively evaluates all valid permutations with pruning. The stored solution is the mathematically proven shortest route for that combination. The only approximation is the snap distance, which decreases monotonically as resolution increases. Route Genome is the first system that returns a TSP solution with a verifiable, quantifiable accuracy bound at query time.
The system immediately returns the best available solution using the current UTRM. In parallel, the precomputation engine fills in missing combinations at higher resolution in the background. Because computation is cumulative and reusable, adding new combinations builds on existing work.
Commercial engines are optimized for real-time heuristic computation — fast and practical, but they don't guarantee optimality and discard every computation. Route Genome's query response is a database lookup in milliseconds, regardless of destination count, with optimal solutions at the stated grid resolution. The two approaches are complementary during transition.
Designed for distributed cloud deployment. Precomputation benefits from parallel processing across any number of compute nodes. Query infrastructure is a standard high-availability database cluster optimized for reads. On-premises deployment is available for sensitive applications where network connectivity cannot be assumed.
Yes. Exclusion zones are a first-class feature defined at grid initialization. Routes never traverse those grid points. Compliance is built into stored solutions, not applied as post-processing. Examples include restricted airspace, military exclusion zones, legally prohibited areas, and active conflict zones.
Because all permutations are precomputed, removing a destination is as simple as retrieving the stored solution for the remaining subset. For drone delivery, if a recipient is unavailable, the optimal route for the updated set is retrieved instantly. For military applications, no communication with a ground station is required.
No. The architecture is agnostic to the meaning of its coordinates. Any problem expressed as points in a coordinate space — network nodes, manufacturing steps, supply chain waypoints — can be modeled on a Route Genome grid. The value is in the precomputation and lookup architecture, not geography-specific logic.
For destination counts beyond the current precomputed maximum, large routes are decomposed into precomputed sub-routes that are stitched together using stored optimal segments. This produces near-optimal solutions with dramatically less computation than traditional solvers. As the UTRM grows, the fully precomputed cutoff rises continuously.
Tiered service model based on grid resolution. Higher resolution at a premium. Because solutions already exist, higher-resolution service requires no additional computation at query time. Volume licensing, API-based access, and on-premises database licensing are all available. Military and enterprise clients may negotiate dedicated UTRM instances.
Protected by patent (pending), trade secret law, and contractual access controls. The database is the product of years of computational investment and cannot be regenerated quickly or cheaply. Access is provided through authenticated API endpoints, not raw data exports. The proprietary precomputation architecture is separately protected.
Drone delivery is one of the most compelling applications. Drones operate in 3D coordinate spaces with hard constraints — airspace restrictions, weather avoidance, battery limits, delivery windows. Route Genome handles all of these natively. As drone networks scale, constant-time query performance becomes increasingly valuable.
Google Maps computes shortest paths between two points in real time — it does not solve multi-destination optimization with mathematical guarantees, and doesn't store solutions for reuse. Route Genome determines the optimal sequence of destinations; a service like Google Maps can then compute turn-by-turn navigation between them. The systems are complementary.
The capability to return a deliberately suboptimal but constrained route — maximizing time in transit rather than minimizing it. Useful when a destination is temporarily unavailable and a vehicle needs to "loiter" productively. For military applications, vehicles can maximize loiter time near a target area until a time-sensitive window opens.
Useful from the moment the first combinations are computed. Hundreds of grids with multiple permutations are immediately deployable. The system delivers value from day one and improves continuously. There is no "cliff" of completeness that must be reached.
Existing solutions are never deleted. The UTRM is cumulative — lower-resolution solutions remain available. Higher-resolution solutions are added alongside them. Every computation ever performed has permanent value and is never discarded.
Yes. The relevant UTRM subset is preloaded onto onboard storage before deployment. Route queries are served locally with no network dependency — same millisecond latency as a networked deployment. Ideal for military drones, autonomous vehicles in remote areas, and maritime vessels.
The UTRM stores routes for combinations of grid points, not for fixed no-go configurations. Updated exclusion lists trigger an immediate re-lookup, not a re-computation. For onboard military applications, the full permutation space is preloaded, so tactical changes produce instantaneous responses.
As grid resolution increases without bound, snap distance approaches zero, and routes approach exact mathematical optimality. In the theoretical limit of infinite resolution, Route Genome returns the exact optimal TSP solution for any real-world coordinates. In practical terms, achievable resolutions will produce snap distances indistinguishable from exact solutions. Route Genome doesn't just approach a solution — it converges on perfection.