How to use it
- Baseline first. Run AS-IS: each quay crane owns three trucks.
- Pool the fleet. TO-BE I sends the nearest idle truck to the least-progressed crane.
- Tune capacity. Change fleet size and the per-crane truck limit; watch queues move.
- Prove the decision. Compare all policies with the same seed, then sweep 10–27 trucks.
Work orders
0 / 1,290
Terminal time
00:00
Truck idle
0%
Avg resource queue
0.0 min
Dual cycles
0
QC utilisation
0%
Live terminal digital twinReady · fixed seed 1
READY
Live event stream
Waiting for simulation…
00:0000:00
Truck carrying discharge
Truck carrying load
Empty / waiting truck
Quay crane
Yard crane
Scenario evidence
All rows use the same work-list and random seed. Lower terminal time and queue are better; dual cycles and utilisation reveal why.
| Policy | YT | Limit | QC speed | Terminal time | Idle | Queue / job | Dual cycles | QC util. |
|---|---|---|---|---|---|---|---|---|
| Run the comparison to create evidence. | ||||||||
Start with AS-IS, then ask: can a pooled fleet deliver the same turnaround with fewer than 27 trucks?
The operations question
A terminal is a coupled queueing network. More trucks can starve neither crane - but too many trucks merely relocate the bottleneck into crane queues. The control rule matters as much as fleet size.
The control logic
TO-BE selects the quay crane with the least completed share, caps trucks already assigned to it, prefers a load/discharge alternation, then chooses the nearest eligible idle truck.
Class challenge
- Find the smallest fleet within 5% of the fastest turnaround.
- Explain the idle-versus-queue trade-off.
- Decide whether faster quay cranes or better dispatch deserves the next dollar.
This is an independent browser-native educational reconstruction - not an embedded AnyLogic runtime. It uses the supplied project’s exact 1,290-row work list, distance matrix, resource counts, timing distributions and published control rules; animation and event engine are original for this Lab. Source model: Container Terminal · 19th Simulation Contest winner.