Work

Tramp Ship Routing and Scheduling with Integrated Carbon Intensity Indicator (CII) Optimization

Year: 2025

Type: article

Abstract: In response to growing environmental concerns and regulatory pressures, reducing carbon emissions in maritime transport has become a priority. Shipping companies face the challenge of balancing profitability objectives with the imperative to minimize their environmental footprint. This study addresses the tramp ship routing and scheduling problem by incorporating the carbon intensity indicator (CII) into the optimization framework. A bi-objective optimization model is developed, with two objective functions aimed at maximizing fleet profit and improving CII ratings. The Gale–Shapley algorithm is employed to achieve stable vessel–cargo matching, and the genetic algorithm is adopted for iterative optimization. This computational study, based on real historical data, verifies the effectiveness of the proposed model and algorithm. The results demonstrate notable improvements in fleet efficiency and environmental performance, increasing profitability by 4.38% while maintaining favorable CII ratings. The findings provide valuable theoretical guidance for shipping companies navigating increasingly stringent CII regulations.

Source: Journal of Marine Science and Engineering

DOI: 10.3390/jmse13040752

Authors: Haiying Yang, Feiyang Ren, Jingbo Yin, Siqi Wang, Rafi Ullah Khan

Institutions: Shanghai Jiao Tong University, State Key Laboratory of Ocean Engineering, China Ocean Shipping (China)

Language: English

Topic: Maritime Transport Emissions and Efficiency

Subfield: Environmental Engineering

Field: Environmental Science

Domain: Physical Sciences

SDGs: Climate action, Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $3,137