Concepts¶
Deep dive into the core concepts behind Waremax simulation.
Overview¶
Understanding these concepts helps you design better simulations and interpret results accurately.
| Section | Topics |
|---|---|
| Simulation Model | DES, time model, events, determinism |
| Warehouse Model | Maps, nodes, edges, storage, stations |
| Robot Operations | Movement, tasks, battery, maintenance |
| Traffic Management | Capacity, congestion, deadlocks |
| Policies | Task allocation, station assignment, batching |
| Metrics & Analysis | KPIs, time series, RCA |
Simulation Model¶
Waremax uses Discrete Event Simulation (DES), an efficient approach that advances time by jumping between events rather than stepping through fixed time intervals.
Key concepts:
- Events - Things that happen (order arrival, robot movement, service completion)
- Event Queue - Priority queue of future events
- Time Advancement - Clock jumps to next event time
- Determinism - Same seed = same results
Learn more about the Simulation Model →
Warehouse Model¶
The warehouse is modeled as a graph with nodes and edges:
- Nodes - Physical locations (aisles, racks, stations)
- Edges - Paths connecting nodes
- Storage - Racks, bins, and inventory
- Stations - Service points for robots
Learn more about the Warehouse Model →
Robot Operations¶
Robots perform tasks by:
- Moving along edges between nodes
- Executing tasks assigned by policies
- Managing battery (if enabled)
- Receiving maintenance (if enabled)
Learn more about Robot Operations →
Traffic Management¶
Traffic is managed through:
- Capacity constraints on nodes and edges
- Congestion handling (waiting or rerouting)
- Deadlock detection and resolution
- Reservation systems for proactive control
Learn more about Traffic Management →
Policies¶
Policies control decision-making:
- Task Allocation - Which robot gets which task
- Station Assignment - Which station services a task
- Batching - How items are grouped
- Priority - How task types are ordered
Metrics & Analysis¶
Waremax provides comprehensive metrics:
- KPIs - Throughput, cycle time, utilization
- Time Series - Metrics over time
- Congestion Data - Hotspot identification
- Root Cause Analysis - Bottleneck detection