The structural shift that created the problem
Over the last two decades global container trade has migrated from a break-bulk dominated industry to one that is predominantly containerised. Today approximately 90% of non-bulk commodities are transported in containers.
Containerisation standardised the transport industry and created massive efficiencies — shipping times cut by approximately 84%, costs improved by approximately 35%. But with that new direction came new challenges. The first real challenge is finding the balance between container utilisation and turn times. The goal is maximum utilisation combined with the shortest possible turn times.
Effective monitoring of container utilisation and turn times enables lines to inject or reduce fleet size. Poor decision-making increases turn times and decreases utilisation — both of which hit the bottom line directly.
“Monitoring container turn times and utilisation gives an indication of fleet performance.”
Why empties are the cost centre worth attacking
As liner companies compete on cost, they need to either maximise revenue through higher freight rates or reduce operating costs. In the current economic environment, the cost side is where the leverage is.
Based on reports published in 2003, the cost of empty container transportation was just under fifteen million dollars across the industry — accounting for 27% of fleet running costs at the time. Today, through improved management and more balanced trades, the cost of running empties has roughly fallen to about a third of what it was. But it remains a huge cost line item for liner carriers to address.
Trade imbalance is structural, not cyclical. In 2003, container traffic from Asia to Europe was about ten times the back-haul volume. In 2004, about half of containers transported to Northern Europe returned empty. The arithmetic of global trade creates empty container routes that no amount of operational discipline can eliminate — only optimisation can minimise.
Why manual planning cannot scale
A typical instance of network flow has approximately 15 different container options, 3.7 million parameters, 1.2 million variables, and around 600 thousand equations. That's the combinatorial space a repositioning coordinator faces every planning cycle.
It takes a coordinator several days to find a workable solution to a repositioning scenario by hand. Coordinators create plans through a trial-and-error approach that relies on the experience and deep domain knowledge of the planner. Typically they have no formal optimisation skills — they're trading off variables they understand against variables they don't.
Manual repositioning plans and container fleet steering are no longer able to cope with the huge number of variables that need to be taken into account.
“Fleet managers should be able to create a full deployment plan quickly.”
What an optimisation engine restructures
The repositioning problem needs to take into account the whole coordination of routes as well as container distribution among all cargo ships across all networks, followed by the costs of each of these routes. The right solution takes all of the following into account and maximises the profit earned during repositioning — always seeking to deliver a plan that repositions equipment fastest and at the lowest cost achievable.
- Liner shipping service construction constraints
- Cargo flows across the full network, not lane-by-lane
- Empty equipment repositioning paths
- Cabotage restrictions and route legality
- Sail-on-service opportunities to combine moves
- Bunker burn for repositioning legs
- Container detention, transhipment, haulage, feeder and discharge costs
What to look for in the system
Optimisation technology is only part of the solution. Equally important is the ability of the platform to fit your processes and handle the fast-paced rhythm of your sales and service teams. Planners need to review optimisation results quickly, modify them easily, and re-optimise periodically — all while releasing work orders for execution.
“Identifies the equipment imbalance spread across various locations and creates a repositioning plan to achieve minimal cost and time.”
- Real-time imbalance calculation across locations
- User-defined and configurable reposition rules
- Reuse of existing route and cost data
- Global visibility — imbalance status per location on a map
- Demand and supply forecasting from historical data
- Powerful optimisation engine for least-cost / least-time solving
- Graphical representation of surplus → deficit moves by cost, volume, region
- Least-cost extraction — comparing minimum cost against planned container moves
- Allocation forecasting — simulating possible allocation from surplus to deficit
Impact on the bottom line
Asset utilisation should be at the forefront of every shipping line stakeholder's mind. Done well, a liner carrier can reduce fleet size and still remain highly profitable. By employing a system support structure like SVM ERO, a carrier can improve container utilisation, improve customer satisfaction, and reduce cost.
By marginally improving the utilisation of a shipping container, shipping lines can save millions of dollars — not only direct cost (bunker, landside) but the ability to do smarter and more profitable business with the same or smaller fleet. These tools must be combined with careful execution; container utilisation is a tension point between operations and commercial.
“Invest in analytics, not additional fleet and equipment.”
Source: www.solverminds.com/2025/10/15/empty-repositioning-optimization/