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Tramp Ship Routing and Scheduling with Integrated Carbon Intensity Indicator (CII) Optimization
by
Yin, Jingbo
, Yang, Haiying
, Ren, Feiyang
, Wang, Siqi
, Khan, Rafi Ullah
in
Air quality management
/ Algorithms
/ bi-objective optimization model
/ Carbon
/ carbon intensity indicator
/ Cargo ships
/ Case studies
/ Climate change
/ Costs
/ Decision making
/ Ecological footprint
/ Economics
/ Efficiency
/ Emissions
/ Energy consumption
/ Environmental auditing
/ Environmental law
/ Environmental management
/ Environmental performance
/ Environmental sustainability
/ Gale–Shapley algorithm
/ genetic algorithm
/ Genetic algorithms
/ Heuristic
/ Integer programming
/ International economic relations
/ Linear programming
/ Literature reviews
/ Marine transportation
/ Optimization
/ Optimization models
/ Profit maximization
/ Profitability
/ Ratings
/ Scheduling
/ Shipping
/ Shipping industry
/ Ships
/ Technology adoption
/ tramp ship routing and scheduling
2025
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Tramp Ship Routing and Scheduling with Integrated Carbon Intensity Indicator (CII) Optimization
by
Yin, Jingbo
, Yang, Haiying
, Ren, Feiyang
, Wang, Siqi
, Khan, Rafi Ullah
in
Air quality management
/ Algorithms
/ bi-objective optimization model
/ Carbon
/ carbon intensity indicator
/ Cargo ships
/ Case studies
/ Climate change
/ Costs
/ Decision making
/ Ecological footprint
/ Economics
/ Efficiency
/ Emissions
/ Energy consumption
/ Environmental auditing
/ Environmental law
/ Environmental management
/ Environmental performance
/ Environmental sustainability
/ Gale–Shapley algorithm
/ genetic algorithm
/ Genetic algorithms
/ Heuristic
/ Integer programming
/ International economic relations
/ Linear programming
/ Literature reviews
/ Marine transportation
/ Optimization
/ Optimization models
/ Profit maximization
/ Profitability
/ Ratings
/ Scheduling
/ Shipping
/ Shipping industry
/ Ships
/ Technology adoption
/ tramp ship routing and scheduling
2025
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Tramp Ship Routing and Scheduling with Integrated Carbon Intensity Indicator (CII) Optimization
by
Yin, Jingbo
, Yang, Haiying
, Ren, Feiyang
, Wang, Siqi
, Khan, Rafi Ullah
in
Air quality management
/ Algorithms
/ bi-objective optimization model
/ Carbon
/ carbon intensity indicator
/ Cargo ships
/ Case studies
/ Climate change
/ Costs
/ Decision making
/ Ecological footprint
/ Economics
/ Efficiency
/ Emissions
/ Energy consumption
/ Environmental auditing
/ Environmental law
/ Environmental management
/ Environmental performance
/ Environmental sustainability
/ Gale–Shapley algorithm
/ genetic algorithm
/ Genetic algorithms
/ Heuristic
/ Integer programming
/ International economic relations
/ Linear programming
/ Literature reviews
/ Marine transportation
/ Optimization
/ Optimization models
/ Profit maximization
/ Profitability
/ Ratings
/ Scheduling
/ Shipping
/ Shipping industry
/ Ships
/ Technology adoption
/ tramp ship routing and scheduling
2025
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Tramp Ship Routing and Scheduling with Integrated Carbon Intensity Indicator (CII) Optimization
Journal Article
Tramp Ship Routing and Scheduling with Integrated Carbon Intensity Indicator (CII) Optimization
2025
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Overview
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.
Publisher
MDPI AG
Subject
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