PortManager

Description

PortManager is a container port terminal management environment where agents schedule cranes, berths, yard storage, and truck/rail departures over a 168-hour (1-week) planning horizon. The simulation models a medium-large port with realistic vessel arrivals, STS crane operations, yard management, gate/rail logistics, and disruption events (storms, labor strikes, customs delays, equipment breakdowns).

Note: this is a synthetic environment that should be tested thoroughly before use in an RL pipeline.

Capabilities

• Multi-step scheduling of vessels, cranes, yard storage, and transportation
• Managing disruption events (storms, labor strikes, equipment failures, customs holds)
• Balancing berth utilization, crane productivity, and yard efficiency
• Coordinating truck and rail departures
• Handling tide-dependent berthing for deep-draft vessels
• Enforcing safety constraints (hazmat segregation, reefer power requirements)

Compute Requirements

No sandbox or special compute required. PortManager is a pure discrete-event simulation that runs in-process.

License

ORLv1.

Tasks

There are 30 training tasks across 6 scenario types:

• Calm Week (5 tasks): Normal operations with minor disruptions
• Storm Season (5 tasks): Two major storms causing crane shutdowns
• Labor Dispute (5 tasks): Partial strike reduces productivity 50%
• Peak Season (5 tasks): 30% more vessel arrivals than normal
• Equipment Aging (5 tasks): Frequent crane breakdowns
• Mixed Cargo (5 tasks): High proportion of reefer and hazmat cargo

And 10 test tasks across 4 scenario types:

• Perfect Storm (3 tasks): Storm + labor dispute + vessel delays + equipment failure
• Mega Vessel Week (3 tasks): Multiple ULCV arrivals competing for deep-draft berths
• Customs Crackdown (2 tasks): Elevated 15% inspection rate blocking yard space
• Cascade Crisis (2 tasks): Multiple delayed vessels causing yard overflow

Each task simulates a 168-hour (1-week) planning horizon with 6-14 vessel arrivals.

Reward Structure

This is a dense, verifiable reward environment. Rewards are computed on each advance_time call. The agent is rewarded for keeping berths occupied, maintaining high crane productivity, completing vessels within target turnaround times, using yard space efficiently, minimizing truck wait times, filling trains before departure, and maintaining safety compliance. Conversely, idle resources, vessel delays, safety violations, and poor utilization are penalized.

Final reward is the mean of all step rewards, clamped to [0, 1]. No LLM graders are used.

Tools

Agents have access to 10 tools:

1. observe_port() - Full snapshot of berths, cranes, yard, gates, rail, weather, disruptions
2. assign_berth(vessel_id, berth_id) - Dock a waiting vessel (validates draft, availability, tide)
3. assign_cranes(vessel_id, crane_ids) - Assign STS cranes to a berthed vessel
4. move_crane(crane_id, berth_id) - Relocate a crane between berths (1 hour)
5. set_yard_plan(vessel_id, yard_block_ids, container_type) - Designate yard blocks for containers
6. dispatch_trucks(count, yard_block_id, gate_id) - Route trucks between yard and gate
7. schedule_train(track_id, yard_block_ids, departure_hour) - Schedule a rail departure
8. advance_time(hours) - Advance simulation 1-12 hours (returns per-step reward)
9. handle_disruption(disruption_id, action) - Respond to active disruptions
10. submit_plan() - End episode and compute final reward

Time Horizon

PortManager is an open-ended, long-horizon environment simulating a full week of port operations. A typical episode involves 40-60 advance_time calls plus observation and action calls.

Other Environment Requirements

There are no further environment requirements; PortManager works out of the box with the OpenReward endpoint without any secrets.

Safety

Agents in PortManager manage a simulated port terminal. The environment does not present direct safety risks as agents only interact with a synthetic simulation through scheduling decisions. No real-world systems, APIs, or data are involved.

The environment includes safety compliance as a reward component, teaching agents to respect IMDG hazmat segregation rules and reefer power requirements.

Citations

@dataset{GRPortManager,
  author    = {General Reasoning Inc. Team},
  title     = {PortManager},
  year      = {2026},
  publisher = {OpenReward},
  url       = {https://openreward.ai/GeneralReasoning/portmanager}
}