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Station Configuration

Configuration for pick, drop, and other stations.

Schema

stations:
  - id: <string>                   # Required
    node: <string>                 # Required
    type: <string>                 # Required
    concurrency: <integer>         # Default: 1
    queue_capacity: <integer>      # Optional (unlimited)
    service_time_s: <ServiceTime>  # Required

Fields

id

Type: string Required: Yes

Unique station identifier.

stations:
  - id: "pick_station_1"

Best practices:

  • Use descriptive names
  • Include zone or area if applicable
  • Avoid spaces and special characters

node

Type: string Required: Yes

Map node where station is located.

stations:
  - id: "S1"
    node: "N100"  # Must match a node ID in the map

type

Type: string Required: Yes Options: pick, drop, inbound, outbound

Station type.

stations:
  - id: "S1"
    node: "0"
    type: pick
Type Description
pick Order picking station
drop Order drop-off station
inbound Receiving station
outbound Shipping station

concurrency

Type: integer Default: 1

Number of robots that can be serviced simultaneously.

stations:
  - id: "S1"
    node: "0"
    type: pick
    concurrency: 3  # Service up to 3 robots at once

queue_capacity

Type: integer Default: unlimited

Maximum robots waiting in queue.

stations:
  - id: "S1"
    node: "0"
    type: pick
    queue_capacity: 10

If not specified, queue is unlimited.

Service Time Configuration

Schema

service_time_s:
  distribution: <string>           # "constant" | "lognormal" | "exponential" | "uniform"
  base: <float>                   # Base service time
  per_item: <float>               # Time per item
  # Lognormal specific:
  base_stddev: <float>
  per_item_stddev: <float>
  # Uniform specific:
  min_s: <float>
  max_s: <float>

Constant Distribution

Fixed service time.

service_time_s:
  distribution: constant
  base: 5.0       # 5 seconds base
  per_item: 2.0   # + 2 seconds per item

Total time: base + (per_item × items)

Lognormal Distribution

Variable service time with right-skewed distribution.

service_time_s:
  distribution: lognormal
  base: 8.0
  base_stddev: 2.0
  per_item: 2.0
  per_item_stddev: 0.5

Realistic - models human operator variability.

Exponential Distribution

Memoryless service time distribution.

service_time_s:
  distribution: exponential
  base: 10.0      # Mean service time

Use for: Queuing theory validation, simple models.

Uniform Distribution

Service time uniformly distributed between min and max.

service_time_s:
  distribution: uniform
  min_s: 3.0
  max_s: 10.0
  per_item: 1.5

Examples

Single Pick Station

stations:
  - id: "pick_1"
    node: "0"
    type: pick
    concurrency: 2
    queue_capacity: 15
    service_time_s:
      distribution: constant
      base: 5.0
      per_item: 2.0

Multiple Stations

stations:
  - id: "pick_zone_a"
    node: "N100"
    type: pick
    concurrency: 3
    queue_capacity: 20
    service_time_s:
      distribution: lognormal
      base: 6.0
      base_stddev: 1.5
      per_item: 1.8
      per_item_stddev: 0.3

  - id: "pick_zone_b"
    node: "N200"
    type: pick
    concurrency: 3
    queue_capacity: 20
    service_time_s:
      distribution: lognormal
      base: 6.0
      base_stddev: 1.5
      per_item: 1.8
      per_item_stddev: 0.3

  - id: "drop_1"
    node: "N50"
    type: drop
    concurrency: 2
    service_time_s:
      distribution: constant
      base: 3.0
      per_item: 1.0

High-Throughput Station

stations:
  - id: "high_volume_pick"
    node: "N150"
    type: pick
    concurrency: 5
    queue_capacity: 30
    service_time_s:
      distribution: exponential
      base: 4.0

Capacity Planning

Estimating Station Capacity

Single station throughput:

Throughput = (concurrency × 3600) / avg_service_time_s

Example:

  • Concurrency: 2
  • Avg service time: 12s (5 base + 2/item × 3.5 items)
  • Throughput: (2 × 3600) / 12 = 600 tasks/hour

Queue Sizing

Recommended queue = 2 × concurrency × (order_rate / stations)

Example:

  • 4 robots typically waiting + buffer
  • queue_capacity: 10-15