Vehicle Capacity Constraints Blueprint

Model multidimensional load limits (weight, volume, items) for vehicles and ensure cumulative load never exceeds capacity at any point in the route.

   
Feature vehicle-capacity-constraints
Category Workflow
Version 1.0.0
Tags capacity-planning, load-management, cvrp, logistics
YAML Source View on GitHub
JSON API vehicle-capacity-constraints.json

Actors

ID Name Type Description
fleet_manager Fleet Manager human Defines vehicle capacities and job load amounts
optimization_engine Optimization Engine system Tracks cumulative load through each route and enforces capacity

Fields

Name Type Required Label Description
vehicle_capacity json Yes Vehicle Capacity  
job_delivery json No Delivery Amount  
job_pickup json No Pickup Amount  
shipment_amount json No Shipment Amount  
current_load json No Current Load  
break_max_load json No Break Max Load  

States

State field: load_status

Values:

State Initial Terminal
empty Yes  
loaded    
in_transit    
over_capacity   Yes

Transitions:

Name From To Actor Condition
  empty loaded optimization_engine  
  loaded in_transit optimization_engine  
  in_transit over_capacity optimization_engine  

Rules

  • consistent_dimensions: All capacity arrays must have the same number of dimensions across vehicles, jobs, and shipments.
  • per_dimension_check: Capacity is checked per dimension independently; every dimension must be within bounds simultaneously.
  • delivery_preloaded: Delivery amounts are pre-loaded onto the vehicle before the route starts and reduced at each delivery stop.
  • pickup_accumulates: Pickup amounts accumulate on the vehicle as pickup stops are served.
  • infeasible_rejection: A route is infeasible if vehicle load exceeds capacity in any dimension at any point; such routes are rejected during construction.
  • break_max_load_rule: If break_max_load is set, a break may only be scheduled when vehicle load is at or below the maximum on all dimensions.
  • zero_capacity: Capacity dimension count of zero means no capacity constraint is applied.

Outcomes

Capacity_exceeded_plan_mode (Priority: 4)

Given:

  • plan/ETA mode is active
  • vehicle load exceeds capacity at some step

Then:

  • emit_event event: route.capacity.violated

Result: Violation of type load recorded in step and route.

Capacity_exceeded_solving (Priority: 5)

Given:

  • route would require vehicle to carry more than capacity on at least one dimension
  • standard solving mode

Then:

  • emit_event event: job.unassigned

Result: Job not added to this vehicle’s route; optimizer tries other vehicles or leaves unassigned.

Break_load_enforced (Priority: 6)

Given:

  • break has max_load defined
  • vehicle load at scheduled break time exceeds break max_load on any dimension

Then:

  • emit_event event: break.rescheduled

Result: Break deferred until load drops below max_load, or reported as max_load violation in plan mode.

Capacity_satisfied (Priority: 10)

Given:

  • sum of pickups minus deliveries does not exceed vehicle capacity on any dimension
  • at every step the running load is within bounds

Then:

  • set_field target: current_load — load after each step recorded in solution
  • emit_event event: route.capacity.valid

Result: Route is feasible; step-level load reported in solution output.

Errors

Code Status Message Retry
CAPACITY_DIMENSION_MISMATCH 400 Capacity arrays have different lengths across vehicles, jobs, or shipments. No
CAPACITY_NEGATIVE_VALUE 400 A capacity or amount value is negative. No

Events

Event Description Payload
route.capacity.valid All stops served within vehicle capacity limits vehicle_id, max_load_reached, dimensions
route.capacity.violated Vehicle load exceeds capacity at a step (plan mode) vehicle_id, step_id, exceeded_dimension, load, capacity
job.unassigned Job could not be placed on any vehicle without violating capacity job_id, reason
break.rescheduled Break deferred due to max_load constraint vehicle_id, break_id, reason
Feature Relationship Reason
vrp-solving required  
multi-vehicle-route-optimization required  
driver-shift-break-constraints optional  
pickup-delivery-pairing recommended  

AGI Readiness

Goals

Reliable Vehicle Capacity Constraints

Model multidimensional load limits (weight, volume, items) for vehicles and ensure cumulative load never exceeds capacity at any point in the route.

Success Metrics:

Metric Target Measurement
processing_time < 5s Time from request to completion
success_rate >= 99% Successful operations divided by total attempts

Constraints:

  • performance (negotiable): Must not block dependent workflows

Autonomy

Level: semi_autonomous

Human Checkpoints:

  • before transitioning to a terminal state

Escalation Triggers:

  • error_rate > 5

Tradeoffs

Prefer Over Reason
reliability speed workflow steps must complete correctly before proceeding

Coordination

Protocol: orchestrated

Consumes:

Capability From Fallback
vrp_solving vrp-solving degrade
multi_vehicle_route_optimization multi-vehicle-route-optimization degrade

Safety

Action Permission Cooldown Max Auto
capacity_satisfied autonomous - -
capacity_exceeded_solving autonomous - -
capacity_exceeded_plan_mode autonomous - -
break_load_enforced autonomous - -
Extensions (framework-specific hints) ```yaml source: repo: https://github.com/VROOM-Project/vroom project: VROOM tech_stack: C++20 files_traced: 6 entry_points: - src/structures/vroom/amount.h - src/structures/vroom/vehicle.h - src/structures/vroom/job.h - src/structures/vroom/break.h ```