Nonlinear programming for fleet deployment, voyage planning and speed optimization in sustainable liner shipping

Author:

Wu Yiwei1,Huang Yadan2,Wang H345,Zhen Lu6

Affiliation:

1. Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong

2. Sino-US Global Logistics Institute, Antai College of Economics and Management, Shanghai Jiao Tong University, Shanghai 200030, China

3. School of Mathematics and Applied Statistics, University of Wollongong, Wollongong, NSW 2522, Australia

4. Strome College of Business, Old Dominion University, Norfolk, VA 23529, USA

5. Faculty of Business, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong

6. School of Management, Shanghai University, Shanghai 200436, China

Abstract

<abstract> <p>Limiting carbon dioxide emissions is one of the main concerns of green shipping. As an important carbon intensity indicator, the Energy Efficiency Operational Index (EEOI) represents the energy efficiency level of each ship and can be used to guide the operations of ship fleets for liner companies. Few studies have investigated an integrated optimization problem of fleet deployment, voyage planning and speed optimization with consideration of the influences of sailing speed, displacement and voyage option on fuel consumption. To fill this research gap, this study formulates a nonlinear mixed-integer programming model capturing all these elements and subsequently proposes a tailored exact algorithm for this problem. Extensive numerical experiments are conducted to show the efficiency of the proposed algorithm. The largest numerical experiment, with 7 ship routes and 32 legs, can be solved to optimality in four minutes. Moreover, managerial insights are obtained according to sensitivity analyses with crucial parameters, including the weighting factor, unit price of fuel, Suez Canal toll fee per ship, weekly fixed operating cost and cargo load in each leg.</p> </abstract>

Publisher

American Institute of Mathematical Sciences (AIMS)

Subject

General Mathematics

Reference58 articles.

1. United States Environmental Protection Agency (USEPA), Sources of greenhouse gas emissions, 2022. Available from: https://www.epa.gov/ghgemissions/sources-greenhouse-gas-emissions.

2. S. S. Young (SSY), Smoke and mirrors: new decarbonisation regulations meet rising emissions, 2022. Available from: https://www.ssyonline.com/our-blog/posts/2022/january-2022/smoke-and-mirrors-new-decarbonisation-regulations-meet-rising-emissions/.

3. International Maritime Organization (IMO), Third IMO greenhouse gas study, 2014. Available from: https://gmn.imo.org/wp-content/uploads/2017/05/GHG3-Executive-Summary-and-Report_web.pdf.

4. United Nations (UN), Paris agreement, 2015. Available from: https://unfccc.int/sites/default/files/english_paris_agreement.pdf.

5. International Maritime Organization (IMO), Initial IMO GHG strategy, 2018. Available from: https://www.imo.org/en/MediaCentre/HotTopics/Pages/Reducing-greenhouse-gas-emissions-from-ships.aspx.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3