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Abstract

Effective route and speed decision-making can significantly reduce vessel operating costs and emissions. However, existing optimization methods developed for conventional fuel-powered vessels are inadequate for application to methanol dual-fuel ships, which represent a new energy vessel type. To address this gap, this study investigates the operational characteristics of methanol dual-fuel liners and develops a mixed-integer nonlinear programming (MINLP) model aimed at minimizing operating costs. Furthermore, an improved genetic algorithm (GA) integrated with the Nonlinear Programming Branch-and-Bound (NLP-BB) method is proposed to solve the model. The case study results demonstrate that the proposed approach can reduce operating costs by more than 15% compared to conventional route and speed strategies while also effectively decreasing emissions of CO2, NOx, SOx, PM, and CO. Additionally, comparative experiments reveal that the designed algorithm outperforms both the GA and the Linear Interactive and General Optimizer (LINGO) solver for identifying optimal route and speed solutions. This research provides critical insights into the operational dynamics of methanol dual-fuel vessels, demonstrating that traditional route and speed optimization strategies for conventional fuel vessels are not directly applicable. This study provides critical insights into the optimization of voyage decision-making for methanol dual-fuel vessels, demonstrating that traditional route and speed optimization strategies designed for conventional fuel vessels are not directly applicable. It further elucidates the impact of methanol fuel tank capacity on voyage planning, revealing that larger tank capacities offer greater operational flexibility and improved economic performance. These findings provide valuable guidance for shipping companies in strategically planning methanol dual-fuel operations, enhancing economic efficiency while reducing vessel emissions.

Details

1009240
Business indexing term
Title
Joint Optimization of Route and Speed for Methanol Dual-Fuel Powered Ships Based on Improved Genetic Algorithm
Author
Zhao, Li 1 ; Zhang, Hao 2   VIAFID ORCID Logo  ; Zhang, Jinfeng 1 ; Wu, Bo 1 

 School of Navigation, Wuhan University of Technology, Wuhan 430000, China; [email protected] (Z.L.); 
 School of Management, Wuhan University of Technology, Wuhan 430000, China; [email protected] 
Publication title
Volume
9
Issue
4
First page
90
Publication year
2025
Publication date
2025
Publisher
MDPI AG
Place of publication
Basel
Country of publication
Switzerland
e-ISSN
25042289
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Online publication date
2025-04-08
Milestone dates
2025-02-06 (Received); 2025-04-01 (Accepted)
Publication history
 
 
   First posting date
08 Apr 2025
ProQuest document ID
3194490294
Document URL
https://www.proquest.com/scholarly-journals/joint-optimization-route-speed-methanol-dual-fuel/docview/3194490294/se-2?accountid=208611
Copyright
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2025-04-25
Database
ProQuest One Academic