Backload Matching

Deploy Backload Matching Engine

Adds a parallel page to the ORS Control App that solves the backload problem for any line-haul fleet with imbalanced lanes: trailers reaching the continent and waiting up to three days for a return load. The page issues a single OPENROUTESERVICE_APP.CORE.OPTIMIZATION(...) call that jointly assigns N idle-bound trailers to a pool of internal volumes (own waiting shipments) and external offers (synthesized in the style of Timocom, WTransnet, Teleroute, B2P), minimizing total empty kilometres. Internal-first preference is encoded as VROOM priority; ADR/equipment gating uses VROOM skills; direction-to-home bias is encoded in each vehicle's end location. Accepted plans are written back to PROPOSAL_DECISIONS to close the Action Engine loop.

The existing Route Optimization and Asset Velocity pages are not modified - Backload is an additive, parallel page.

Use Case Narrative

See references/use-case-narrative.md for the full story. Summary anchored in the May 5 NTBO call with DHL Freight (Volker Nachtsheim / Martin Ahleff) and the Asset Velocity Case 4 slide:

• ~2,500 trailers, ~100 Nordic dispatchers, ~20 new orders/min across Europe.
• Trailers reach the continent and wait up to 3 days in Paris for backloads.
• Today: manual portal-hopping across Timocom, WTransnet, Teleroute, B2P.
• Desired: fleet-wide "give me a structural plan for tomorrow" - internal-first, external-second.
• Generalises 1:1 to Maersk Inland, K+N Road, DSV, XPO, Geodis, Dachser, FedEx Freight, Schneider, J.B. Hunt - anyone with imbalanced lanes.

Prerequisites

• install-fleet-apps deployed (OPENROUTESERVICE_APP database with all ORS services running). The demo runs against whatever region/vehicle preset is currently active in the Control App - no specific region required.
• route-optimization deployed.
• Synthetic datasets seeded under SYNTHETIC_DATASETS.UNIFIED.* (DIM_FLEET, FACT_TRIPS) - not strictly required for the page, but kept as a dependency since this skill was scoped against that dataset.
• Run Data Studio for the target (region, vehicle_type) first so V_DIM_FLEET_CURRENT, V_DIM_POIS_CURRENT, and V_FACT_FREIGHT_OFFERS_CURRENT are populated. The page no longer has an in-page "Generate seed data" action.

Required Privileges

Note: ACCOUNTADMIN is NOT required.

Configuration

Error Logging

Follow the Error Logging convention in AGENTS.md. Log file prefix: backload-matching.

Workflow

Step 1: Set Query Tag

ALTER SESSION SET query_tag = '{"origin":"sf_sit-is-fleet","name":"oss-backload-matching","version":{"major":1,"minor":0},"attributes":{"is_quickstart":1,"source":"sql"}}';

Step 2: Verify Prerequisites

SHOW SERVICES IN DATABASE OPENROUTESERVICE_APP;            -- 4 services RUNNING
SELECT COUNT(*) FROM SYNTHETIC_DATASETS.UNIFIED.V_FACT_FREIGHT_OFFERS_CURRENT;  -- > 0
DESC FUNCTION OPENROUTESERVICE_APP.CORE.OPTIMIZATION(VARIANT, VARCHAR);     -- exists

If any step fails, deploy the upstream skill first.

Step 3: Run Bootstrap

Run references/bootstrap.sql from the active connection:

snow sql -f .cortex/skills/backload-matching/references/bootstrap.sql -c <ACTIVE_CONNECTION>

This creates FLEET_INTELLIGENCE.BACKLOAD_MATCHING.{CONFIG, VW_TRAILERS, VW_INTERNAL_VOLUMES, VW_EXTERNAL_OFFERS, PROPOSAL_DECISIONS} as projection views over SYNTHETIC_DATASETS.UNIFIED.* filtered by the active Data Studio preset (CONFIG row).

The active preset is auto-synced when the user switches in DatasetPicker (or runs a new Data Studio job) - same pattern that fleet-intelligence-ebike, dwell-analysis, and route-deviation use.

Step 3b (one-time, existing accounts only): Backfill freight offers

Data Studio jobs created BEFORE the v1.0.199 control app rollout did not generate SYNTHETIC_DATASETS.UNIFIED.FACT_FREIGHT_OFFERS. Backfill them once:

snow sql -f .cortex/skills/backload-matching/references/backfill-freight-offers.sql -c <ACTIVE_CONNECTION>

Idempotent: skips regions that already have offers. New presets generated after v1.0.199 deploy will populate offers natively, so this script is a no-op on greenfield deployments.

Step 3c: Cockpit schema (Backload Proposals)

Run references/proposals-schema.sql AFTER bootstrap.sql. It adds the neutral cockpit layer to FLEET_INTELLIGENCE.BACKLOAD_MATCHING:

snow sql -f .cortex/skills/backload-matching/references/proposals-schema.sql -c <ACTIVE_CONNECTION>

Creates MATCH_PARAMS (config-driven, vehicle-class-generalized constraints - distance / pickup-date / horizon / weight-fit / hazmat; no FTL-specific ADR/Thermo/Mega/LDM), VW_LOADS (internal volumes + external offers as one demand pool with an IS_INTERNAL priority flag), VW_TRAILERS_GEO (idle-vehicle free point + return-to-home geometry, free time anchored to the live "now" window), VW_CANDIDATES + VW_CANDIDATES_SCORED (per-rule pass/fail explainability), and empty PROPOSALS / FEEDBACK tables. All are synthetic-backed projections filtered by the active CONFIG preset. Sanity report prints row counts at the end.

Step 4: Interactive pages (FLEET_SA_APP)

Two config-registered views ship in FLEET_SA_APP (category Optimization), both reading the neutral FLEET_APP.BACKLOAD_MATCHING + FLEET_INTELLIGENCE.BACKLOAD_MATCHING views and solving live via the /api/backload/solve contract seam. They render an empty state until Steps 3/3c have been run for the active preset.

• Backload Matching (backload_matching) - single-solve engine: idle vehicles + internal loads + external offers, internal-first VROOM, assignment cards + KPIs + map, write-back to PROPOSAL_DECISIONS.
• Backload Proposals (backload_proposals) - the advanced multi-strategy cockpit: run Quick scan / Per-load VRP / Fleet 1:1 / Profit-max, or Ensemble to fuse all four into one graded (A..F), internal-first proposal per vehicle. Adjustable ranking weights, per-constraint pass/fail chips from VW_CANDIDATES_SCORED, a Cortex rationale, and session-only Accept/Reject/Flag (no write-back).

The generic, use-case-agnostic vrp_solve User verb (backed by ROUTING_TOOLS.TOOL_VRP_SOLVE) lets the Cortex agent solve any prepared VROOM challenge; the app itself uses /api/backload/solve (robust raw-scalar seam that avoids the TVF 0-row trap).

Step 5: Verify

1. Set the region/vehicle preset you want to demo (default: SanFrancisco/ebike). Both pages read BACKLOAD_MATCHING.CONFIG, auto-synced to the active preset.
2. Open Backload Proposals (sidebar, Optimization). Confirm the counts strip shows idle vehicles, internal loads, external offers, and eligible pairs > 0.
3. Leave strategy on Ensemble, click Run proposals. Within ~10-40 sec (VROOM must be running for the active region) the page renders per-vehicle graded cards, KPIs (vehicles matched / internal filled / empty km / avg score), and the empty+loaded legs on the map.
4. Expand a card to see the per-constraint pass/fail chips and alternative loads; click Explain (Cortex) for a rationale; use Accept/Reject/Flag (session-only).
5. Open Backload Matching for the single-solve variant; Match backloads then Accept & write decisions persists to PROPOSAL_DECISIONS.

Step 6: AISQL Notebook (optional)

Upload assets/notebooks/backload-matching-aisql.ipynb to a notebook stage and walk through the AI_FILTER / AI_AGG / AI_CLASSIFY / AI_EXTRACT / Cortex Complete cells. The notebook re-uses the same tables and shows the AISQL parity to the page, plus the raw VROOM JSON the page sends to OPTIMIZATION.

Cleanup

DROP VIEW   IF EXISTS FLEET_INTELLIGENCE.BACKLOAD_MATCHING.VW_CANDIDATES_SCORED;
DROP VIEW   IF EXISTS FLEET_INTELLIGENCE.BACKLOAD_MATCHING.VW_CANDIDATES;
DROP VIEW   IF EXISTS FLEET_INTELLIGENCE.BACKLOAD_MATCHING.VW_TRAILERS_GEO;
DROP VIEW   IF EXISTS FLEET_INTELLIGENCE.BACKLOAD_MATCHING.VW_LOADS;
DROP TABLE  IF EXISTS FLEET_INTELLIGENCE.BACKLOAD_MATCHING.FEEDBACK;
DROP TABLE  IF EXISTS FLEET_INTELLIGENCE.BACKLOAD_MATCHING.PROPOSALS;
DROP TABLE  IF EXISTS FLEET_INTELLIGENCE.BACKLOAD_MATCHING.MATCH_PARAMS;
DROP VIEW   IF EXISTS FLEET_INTELLIGENCE.BACKLOAD_MATCHING.VW_EXTERNAL_OFFERS;
DROP VIEW   IF EXISTS FLEET_INTELLIGENCE.BACKLOAD_MATCHING.VW_INTERNAL_VOLUMES;
DROP VIEW   IF EXISTS FLEET_INTELLIGENCE.BACKLOAD_MATCHING.VW_TRAILERS;
DROP TABLE  IF EXISTS FLEET_INTELLIGENCE.BACKLOAD_MATCHING.PROPOSAL_DECISIONS;
DROP TABLE  IF EXISTS FLEET_INTELLIGENCE.BACKLOAD_MATCHING.CONFIG;
DROP SCHEMA IF EXISTS FLEET_INTELLIGENCE.BACKLOAD_MATCHING;

Note: this skill does NOT delete from SYNTHETIC_DATASETS.UNIFIED.FACT_FREIGHT_OFFERS since that table is owned by install-fleet-apps (Data Studio output) and is shared. Use the cleanup script in install-fleet-apps if you also want to remove the freight-offer data per preset.

The Control App image rollback is handled by re-deploying the previous image tag from the registry; the new page becomes inaccessible automatically when the schema is dropped (the page surfaces an empty state).

Out of Scope

• Live Timocom / WTransnet / Teleroute / B2P API integration (synthetic only - productisation note in references/optimization-vrp-mapping.md).
• Asset Velocity 7-day idle alerting / email engine (the existing Asset Velocity tab covers KPIs; this skill stays focused on the solver).
• DGF / myDHLI POD-map use case.
• Real-time streaming pipeline (we ship a polled view first; productisation: Snowpipe Streaming for EXTERNAL_OFFERS).