Roughly 60% of the world's oil is transported by tanker — and the schedules that move it are still mostly built by hand. Solverminds' tanker stack pairs the operational ERP backbone used across our liner deployments with an AI-powered fleet optimiser built specifically for oil tanker scheduling.
The fleet
Tanker class is dictated by the routes and canals a vessel needs to traverse. Each class has its own port-access and route-feasibility profile — none of which is optional to model in the schedule.
The scheduling problem
These are not hypothetical. They are the standing list every tanker planner works against, every 90-day window. Each one is a place the schedule can break before the first vessel sails.
A 90-day schedule across multiple vessels, multi-grade cargo and multiple load and discharge ports is time-consuming to assemble by hand.
Stocks must never dip below minimum safety levels — across volatile, holiday- and weather-influenced consumption patterns.
Congestion, vessel breakdown, berth maintenance, planned off-hires, arrival at specific port windows.
Daily consumption per grade per discharge port shifts with holidays, season and weather. None of it is smooth.
Planners maximise TC utilisation while respecting draft, air draft, LOA, beam, vessel age, vessel flag and dry-docking constraints.
Each loaded grade must be compatible with the previous voyage, or tank cleaning time has to be scheduled in.
Finding spot tonnage when the available fleet is fully deployed, before supply is interrupted.
Single-berth availability, daytime-only arrivals, draft limitations, tidal ranges, waiting time, flag-age restrictions, port maintenance.
Adverse weather, strikes, blocked canals, accidents, country unrest — and the rebuilds they force on the plan.
Management asks for maximum vessel and berth utilisation simultaneously with the lowest possible cost.
The response
The Tanker Fleet and Service Optimizer pairs an optimisation engine with machine learning. ML generates demand forecasts per grade per discharge port; the optimiser produces a schedule against that forecast while respecting every constraint above. The objectives are explicit: minimise cost, satisfy demand at the discharge port, maximise time-charter utilisation.
Open the product pageThe platform underneath
Tanker operations share most of their operational ground with the rest of liner shipping — scheduling, bunker, chartering, port operations. The optimiser sits on top of that backbone rather than replacing it.
Proforma rotations across multiple vessels and load / discharge ports. Same scheduling backbone deployed across container, breakbulk and tanker fleets.
Real-time bunker tracking, predictive consumption, auto Bunker Delivery Notes. Bunker is the dominant cost line for any vessel operator — tankers are no exception.
Time-charter and voyage-charter lifecycles, hire / off-hire / dry-dock tracking, broker-free transactions across the fleet.
Port-call workflow, agency disbursement reconciliation, vendor contracts — the operational ground truth behind every voyage.
Where the value lands
The headline objective is minimised cost of operations. Underneath that, the optimiser ensures demand is satisfied and no port runs dry, maximises vessel utilisation, minimises waiting time at port due to tide, congestion, maintenance and dry-docking, allows replanning after any disruption at the discharge port or in transit, facilitates selection and allocation of time-chartered and spot-chartered vessels at the load region, and ensures every technical port and vessel constraint is met.
Cost
Minimise total cost of operations
Reliability
Demand satisfied, no port runs dry
Utilisation
Maximise time-charter productivity
Resilience
Replan in minutes after disruption
Grade rules
Compatibility & tank cleaning honoured
Constraints
Every port / vessel rule respected
The ten challenges and twelve features on this page come straight from the published Solverminds whitepaper. Open it for the full version — including how the optimiser handles multi-grade loading, spot charter, and disruption replanning.