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

Yiwei Wu; Yadan Huang; H Wang; Lu Zhen; Yiwei Wu; Yadan Huang; H Wang; Lu Zhen

doi:10.3934/era.2023008

Electronic Research Archive

2023, Volume 31, Issue 1: 147-168. doi: 10.3934/era.2023008

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

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

Received: 04 August 2022 Revised: 20 September 2022 Accepted: 22 September 2022 Published: 26 October 2022

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.
- fleet deployment optimization,
- EEOI,
- maritime decarbonization,
- voyage planning,
- carbon dioxide emission
Citation: Yiwei Wu, Yadan Huang, H Wang, Lu Zhen. Nonlinear programming for fleet deployment, voyage planning and speed optimization in sustainable liner shipping[J]. Electronic Research Archive, 2023, 31(1): 147-168. doi: 10.3934/era.2023008

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Abstract

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.

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