<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This paper constructs a mathematical model of the C-W saving algorithm based on the characteristics of the C-W saving algorithm and the collection and data analysis of energy efficiency data of ships without time window constraints. On this basis, the mathematical model with the time window constraint is further constructed by adding the time window constraint and fully considering some factors in the transportation of inland vessels that cannot be ignored, such as fuel price, carbon tax price and sailing speed. Finally, the impact of fuel, charter, and carbon tax prices on the optimization scheme is analyzed by the sensitivity analysis method. With the lowest total sailing cost as the target, the total sailing cost of the whole voyage is reduced by $4,749, which is 3.75% less than last year. Optimization with the lowest carbon emission as the goal, the whole voyage CO<sub>2</sub> emissions reduced by 4.22t, a year-on-year reduction of 10.76%. Considering the total voyage cost and carbon emission for multi-objective optimization, the total voyage cost is reduced by 1210, which is 0.91% less than the same period last year. Therefore, the speed optimization method for inland sea vessels based on the C-W saving algorithm can provide a basis for shipowners and speed companies in making sailing plans.</p>
</abstract>

This paper constructs a mathematical model of the C-W saving algorithm based on the characteristics of the C-W saving algorithm and the collection and data analysis of energy efficiency data of ships without time window constraints. On this basis, the mathematical model with the time window constraint is further constructed by adding the time window constraint and fully considering some factors in the transportation of inland vessels that cannot be ignored, such as fuel price, carbon tax price and sailing speed. Finally, the impact of fuel, charter, and carbon tax prices on the optimization scheme is analyzed by the sensitivity analysis method. With the lowest total sailing cost as the target, the total sailing cost of the whole voyage is reduced by $4,749, which is 3.75% less than last year. Optimization with the lowest carbon emission as the goal, the whole voyage CO2 emissions reduced by 4.22t, a year-on-year reduction of 10.76%. Considering the total voyage cost and carbon emission for multi-objective optimization, the total voyage cost is reduced by 1210, which is 0.91% less than the same period last year. Therefore, the speed optimization method for inland sea vessels based on the C-W saving algorithm can provide a basis for shipowners and speed companies in making sailing plans.

Speed optimization of inland sea vessels based on C.W saving algorithm

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

{"article-title":"Speed optimization of inland sea vessels based on C.W saving algorithm"}

This paper constructs a mathematical model of the C-W saving algorithm based on the characteristics of the C-W saving algorithm and the collection and data...

Speed optimization of inland sea vessels based on C.W saving algorithm

Pubblicato online: 30 ago 2023

Pagine: -

Ricevuto: 20 set 2022

Accettato: 10 mar 2022

DOI: https://doi.org/10.2478/amns.2023.2.00271

Parole chiave
Ship speed optimization, C-W saving algorithm, Time window constraint, Sensitivity analysis, Navigation cost

© 2023 Tianyu Liu, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Speed optimization of inland sea vessels based on C.W saving algorithm

Pubblicato online: 30 ago 2023

Pagine: -

Ricevuto: 20 set 2022

Accettato: 10 mar 2022

DOI: https://doi.org/10.2478/amns.2023.2.00271

Parole chiaveShip speed optimization, C-W saving algorithm, Time window constraint, Sensitivity analysis, Navigation cost

© 2023 Tianyu Liu, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Parole chiave
Ship speed optimization, C-W saving algorithm, Time window constraint, Sensitivity analysis, Navigation cost