Cloud Optimization v1 API - Class ShipmentModel (2.4.0)

Reference documentation and code samples for the Cloud Optimization v1 API class ShipmentModel.

A shipment model contains a set of shipments which must be performed by a set of vehicles, while minimizing the overall cost, which is the sum of:

• the cost of routing the vehicles (sum of cost per total time, cost per travel time, and fixed cost over all vehicles).
• the unperformed shipment penalties.
• the cost of the global duration of the shipments

Deprecated: No longer used. Set of break rules used in the model. Each vehicle specifies the BreakRule that applies to it via the [Vehicle.break_rule_indices][google.cloud.optimization.v1.Vehicle.break_rule_indices] field (which must be a singleton).

Specifies duration and distance matrices used in the model. If this field is empty, Google Maps or geodesic distances will be used instead, depending on the value of the use_geodesic_distances field. If it is not empty, use_geodesic_distances cannot be true and neither duration_distance_matrix_src_tags nor duration_distance_matrix_dst_tags can be empty.

Usage examples:

• There are two locations: locA and locB.
• 1 vehicle starting its route at locA and ending it at locA.
• 1 pickup visit request at locB.

model {
  vehicles { start_tags: "locA"  end_tags: "locA" }
  shipments { pickups { tags: "locB" } }
  duration_distance_matrix_src_tags: "locA"
  duration_distance_matrix_src_tags: "locB"
  duration_distance_matrix_dst_tags: "locA"
  duration_distance_matrix_dst_tags: "locB"
  duration_distance_matrices {
    rows {  # from: locA
      durations { seconds: 0 }   meters: 0    # to: locA
      durations { seconds: 100 } meters: 1000 # to: locB
    }
    rows {  # from: locB
      durations { seconds: 102 } meters: 990 # to: locA
      durations { seconds: 0 }   meters: 0   # to: locB
    }
  }
}

• There are three locations: locA, locB and locC.
• 1 vehicle starting its route at locA and ending it at locB, using matrix "fast".
• 1 vehicle starting its route at locB and ending it at locB, using matrix "slow".
• 1 vehicle starting its route at locB and ending it at locB, using matrix "fast".
• 1 pickup visit request at locC.

model {
  vehicles { start_tags: "locA" end_tags: "locB" start_tags: "fast" }
  vehicles { start_tags: "locB" end_tags: "locB" start_tags: "slow" }
  vehicles { start_tags: "locB" end_tags: "locB" start_tags: "fast" }
  shipments { pickups { tags: "locC" } }
  duration_distance_matrix_src_tags: "locA"
  duration_distance_matrix_src_tags: "locB"
  duration_distance_matrix_src_tags: "locC"
  duration_distance_matrix_dst_tags: "locB"
  duration_distance_matrix_dst_tags: "locC"
  duration_distance_matrices {
    vehicle_start_tag: "fast"
    rows {  # from: locA
      durations { seconds: 1000 } meters: 2000 # to: locB
      durations { seconds: 600 }  meters: 1000 # to: locC
    }
    rows {  # from: locB
      durations { seconds: 0 }   meters: 0    # to: locB
      durations { seconds: 700 } meters: 1200 # to: locC
    }
    rows {  # from: locC
      durations { seconds: 702 } meters: 1190 # to: locB
      durations { seconds: 0 }   meters: 0    # to: locC
    }
  }
  duration_distance_matrices {
    vehicle_start_tag: "slow"
    rows {  # from: locA
      durations { seconds: 1800 } meters: 2001 # to: locB
      durations { seconds: 900 }  meters: 1002 # to: locC
    }
    rows {  # from: locB
      durations { seconds: 0 }    meters: 0    # to: locB
      durations { seconds: 1000 } meters: 1202 # to: locC
    }
    rows {  # from: locC
      durations { seconds: 1001 } meters: 1195 # to: locB
      durations { seconds: 0 }    meters: 0    # to: locC
    }
  }
}

Tags defining the destinations of the duration and distance matrices; duration_distance_matrices(i).rows(j).durations(k) (resp. duration_distance_matrices(i).rows(j).meters(k)) defines the duration (resp. the distance) of the travel from visits with tag duration_distance_matrix_src_tags(j) to visits with tag duration_distance_matrix_dst_tags(k) in matrix i.

Tags correspond to [VisitRequest.tags][google.cloud.optimization.v1.Shipment.VisitRequest.tags] or [Vehicle.start_tags][google.cloud.optimization.v1.Vehicle.start_tags]. A given VisitRequest or Vehicle must match exactly one tag in this field. Note that a Vehicle's source, destination and matrix tags may be the same; similarly a VisitRequest's source and destination tags may be the same. All tags must be different and cannot be empty strings. If this field is not empty, then duration_distance_matrices must not be empty.

Tags defining the sources of the duration and distance matrices; duration_distance_matrices(i).rows(j) defines durations and distances from visits with tag duration_distance_matrix_src_tags(j) to other visits in matrix i.

Tags correspond to [VisitRequest.tags][google.cloud.optimization.v1.Shipment.VisitRequest.tags] or [Vehicle.start_tags][google.cloud.optimization.v1.Vehicle.start_tags]. A given VisitRequest or Vehicle must match exactly one tag in this field. Note that a Vehicle's source, destination and matrix tags may be the same; similarly a VisitRequest's source and destination tags may be the same. All tags must be different and cannot be empty strings. If this field is not empty, then duration_distance_matrices must not be empty.

The "global duration" of the overall plan is the difference between the earliest effective start time and the latest effective end time of all vehicles. Users can assign a cost per hour to that quantity to try and optimize for earliest job completion, for example. This cost must be in the same unit as [Shipment.penalty_cost][google.cloud.optimization.v1.Shipment.penalty_cost].

If unset, 00:00:00 UTC, January 1, 1971 (i.e. seconds: 31536000, nanos: 0) is used as default.

Global start and end time of the model: no times outside of this range can be considered valid.

The model's time span must be less than a year, i.e. the global_end_time and the global_start_time must be within 31536000 seconds of each other.

When using cost_per_*hour fields, you might want to set this window to a smaller interval to increase performance (eg. if you model a single day, you should set the global time limits to that day). If unset, 00:00:00 UTC, January 1, 1970 (i.e. seconds: 0, nanos: 0) is used as default.

Gets whether the "max_active_vehicles" field is set

Constrains the maximum number of active vehicles. A vehicle is active if its route performs at least one shipment. This can be used to limit the number of routes in the case where there are fewer drivers than vehicles and that the fleet of vehicles is heterogeneous. The optimization will then select the best subset of vehicles to use. Must be strictly positive.

Set of precedence rules which must be enforced in the model.

Sets of incompatible shipment_types (see ShipmentTypeIncompatibility).

Sets of shipment_type requirements (see ShipmentTypeRequirement).

Set of shipments which must be performed in the model.

Transition attributes added to the model.

Set of vehicles which can be used to perform visits.