Containership Speed Research Articles

Data Analysis and Decision on Navigation Safety of Yangshan Port Channel

Aiming at the problem of pilotage disruption under high wind control, this paper provides statistics on wind direction and wind levels during high wind control days, measures pilotage disruption at Yangshan Port for a total of ten years (from 2011 to 2020), notes the wind direction and wind levels that trigger pilotage disruption, and models and analyzes the effects of different wind directions and wind-level coupling on pilotage disruption. In addition, the difference of traffic flow in the alert area under normal and interrupted conditions of pilotage is analyzed by combining pilotage interruption data and the observation data of the alert area. The law of traffic volume and speed of container ships of different lengths is also analyzed. Based on the data of each observation line, the speed and time of ships in the warning area were evaluated by combining the speed, heading, and time from the records. The traffic law of different types of ships are summarized; that is, the ship’s speed in the caution area is roughly positively correlated with its length: the longer the ship’s length, the faster the ship’s speed, and the less the sailing time. The article provides a basis for the research of pilotage safety operations.

Effects of container ship speed on CO2 emission, cargo lead time and supply chain costs

This article studies ship speed from the supply chain perspective to examine its overall effects on liner operators, customers and environment. A model is proposed to simulate container flows on the Trans-Atlantic trade via a liner service. A striking point is that we not only exploit conventional data of shipping operators but also shipment data of customers to support decision-making processes in maritime supply chains. Our simulation reveals that sailing speed only affects one-fourth of the total supply chain costs, but half of the cargo lead time and over 70% of the carbon footprint. Slow steaming brings about fuel saving and less CO2 emission but extends the transit time of goods and raises inventory carrying cost for customers. This hidden cost is a barrier against deploying mega ships, although they can lower shipping cost and CO2 emission. The simulation also implies the potential of express routes to serve premium shipments, for example medical supplies in times of pandemic and for other essential needs, as well as higher value perishable food.

Sailing Speed and Fleet Deployment Optimization for Intercontinental Container Liner Shipping Considering Cargo Time Value

Abstract This article collectively addresses the issues of optimizing the sailing speed of containerships and fleet deployment in intercontinental container liner shipping, taking cargo time values into consideration. A mixed-integer nonlinear programming model is developed to maximize the gross profits of a container shipping line. The sailing speed is divided into 0.1 knot intervals and a reciprocal-discretization method is proposed to transform the model into an integer-based linear programming model, which can be solved using optimization solvers such as CPLEX. A case study is conducted based on the Far East-West America liner route of a global container shipping line to assess the effectiveness of the proposed model and the reciprocal-discretization method. The results show that when the cargo time value is taken into consideration, the increased sailing speed of containerships on long legs and the decreased number of deployed containerships will generate greater operating profits for the container shipping line. The rise in bunker price will lead to a stepwise decline in sailing speed of containerships and a stepwise growth in the number of deployed containerships. Moreover, the downward trend of sailing speed due to the increase of bunker price will be somewhat delayed as the unit container cargo value increases. Several useful insights are drawn from analysis of the results.

A new model for the calculation of the bunker fuel speed–consumption relation

This paper investigates the relationship between bunker fuel consumption and the speed of container ships. Although there are different models existing in the literature and in the industry, they do not always seem to match the actual maritime conditions. The existing models work well in middle speed levels, but they fail at the low- and high-speed ends unless the parameters in the exponent of the function are changed. Besides the problem of missing a general formulation, the parameters seem to change with speed. Therefore, in this paper a new approach is introduced to illustrate the dependance between bunker fuel consumption and speed, and it is tested by formulating the exponent of the function variable. Stochastic criteria are used to compare the new generalized model with common models using real operating data.

Simulation of Fuzzy PID Control for a Large Containership Speed at Slow Steaming Condition

In this paper, a cycle mean value engine model was built, and the ship propulsion system model was developed by combining the engine model with propeller and ship model following a modular approach in MATLAB/Simulink environment. In addition, the fuzzy PID control theory was investigated and applied in the ship speed intelligent control system under different disturbance circumstances with emphasis at slow steaming condition. Finally, the simulation results indicate that the fuzzy PID controller can improve the dynamic performance of the ship speed control system, decrease oscillation as well as increase response speed.

Sailing speed optimization for container ships in a liner shipping network

This paper first calibrates the bunker consumption – sailing speed relation for container ships using historical operating data from a global liner shipping company. It proceeds to investigate the optimal sailing speed of container ships on each leg of each ship route in a liner shipping network while considering transshipment and container routing. This problem is formulated as a mixed-integer nonlinear programming model. In view of the convexity, non-negativity, and univariate properties of the bunker consumption function, an efficient outer-approximation method is proposed to obtain an ε-optimal solution with a predetermined optimality tolerance level ε. The proposed model and algorithm is applied to a real case study for a global liner shipping company.

The effect of oil price on containership speed and fleet size

The changing prices of bunker fuel open the door for substantial cost savings by adjusting the sailing speed of ships. A large ship may be burning up to 100 000 USD of bunker fuel per day, which may constitute more than 75% of its operating costs. Reducing the cruising speed by 20% reduces daily bunker consumption by 50%. However, in order to maintain liner service frequency and capacity, reducing the cruising speed may require additional ships to operate a route. We construct a cost model that we use to analyse the trade-off between speed reduction and adding vessels to a container line route, and devise a simple procedure to identify the sailing speed and number of vessels that minimize the annual operating cost of the route. Using published data, we demonstrate the potential for large-cost savings when one operates close to the minimal-cost speed. The presented methodology and procedure are applicable for any bunker fuel price.