Digital Fleet Management


Our ADP tool is the foundation of the overall model. The tool matches the Long and Short positions in the client’s portfolio, including FOB and DES cargos, providing an optimal fleet deployment plan. The client can feed-in his contract portfolio and fleet information through on API or upload it in Excel. Price assumptions for single hubs or contracts can also be uploaded and edited by the client – however, we also provide forward curves for the liquid hubs and markets. The ADP tool reacts dynamically to any changes – the overall optimality is determined anew as soon as a contract is modified or added – or any other constraint changed. For product and market specific information, please refer to our product pages for X-LNG, X-Oil, X-Coal.

Vessel Optimisation

The tanker optimisation is a sub-model that calculates the optimal in-voyage adjustments for an individual vessel. For LNG tankers it entails elements such as bunker fuel optimisation, BOG optimisation, cost-optimal cool-down management. These calculations also feed into the ADP and are fully considered for the optimality of its solution.

Route Optimisation

We use multiple distance matrices to provide optimal but also alternative routes between every pair of loading and discharge ports. We give a lot of attention to the details: a vessel without an ice-class classification can’t traverse the Northeast Passage and not every supertanker can access all existing berths. Optimal journey speed is determined economically for every single vessel but constrained through contractual time windows, to keep idle times to a minimum. Weather and security risks, the probability of waiting times at channels and ports are also reflected in the model.


Portfolio Optimisation

Stochastic Optimisation

Besides an optimal routing plan, the model’s output also consists of an optimal trading strategy. When applying a stochastic optimisation approach, the optimality criteria can be aligned to get the most robust trading strategy for a specified price range. The approach also enables the user to access the intrinsic and extrinsic value of the portfolio, as well as its hedge. For the portfolio optimisation we undertake a futures-based price modelling, using Monte Carlo Simulations to model price variations.

Risk Management

We provide commonly used risk metrics such as Value-at-Risk or Profit-at-Risk as well as the full profit and cost distributions for the proposed trading strategies. Additional stochastic risks beyond the price variations, can also be included in the model concerning meteorological conditions, traffic jams (at Panama or Suez), piracy and security issues, etc.

Integration of Gas & LNG Portfolios (only available for X-LNG)

While X-LNG is a model specifically developed for LNG shipping and trading, it includes a Gas market add-on to value the LNG beyond arrival at the discharge port. The model evaluates the profitability of re-gasification upon arrival, storage, or direct sales in liquid form.