Multi-site operator managing 26,000+ container locations daily
Vessel and yard planning with thousands of simultaneous constraints
High-volume loading/unloading requiring stability and efficiency
Solve NP-hard optimization for real-time operational decisions
Cranes and trucks overused or idle during peaks
Manual placement hard to balance under time pressure
Traditional methods too slow for 10,000+ containers
Space, safety, handling, resources conflicted constantly
Manual cycles slowed response to changing conditions
Learns from rewards/penalties in simulated environments
Evaluates placement actions for long-term benefits
Generates plans for 1,000 containers in ~1 minute
Weights stability, yard efficiency, resource use
Considers crane/truck availability in decisions
Connects seamlessly to operational systems
Implements AI logic, data pipelines, integrations
Trains deep reinforcement learning models
Deep Q-Network for placement decisions
Connects optimization engine to operational systems
Prepares operational data for model inputs
Simulation to live deployment and tuning
10% improvement through optimized weight distribution
10% gains from reduced unnecessary movements
1,000 containers optimized in ~1 minute
Planners focus on review, not manual calculation
Combined stability, moves, and resource improvements
Safer vessels with predictable fuel and handling
Fewer moves through intelligent placement
Real-time support for operational cycles
Focus shifts to strategy and adjustments
Handles growing volumes and complexity
You’re one step away from building great software. This case study will help you learn more about how Simform helps successful companies extend their tech teams.
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You’re one step away from building great software. This case study will help you learn more about how Simform helps successful companies extend their tech teams.
