An epsilon-constraint-based exact multi-objective optimization approach for the ship schedule recovery problem in liner shipping

An epsilon-constraint-based exact multi-objective optimization approach for the ship schedule recovery problem in liner shipping

Elmi, Zeinab (Florida State University)
Li, Bokang (Florida State University)
Liang, Benbu (TU Delft System Engineering; Wuhan University of Technology)
Lau, Yui yip (The Hong Kong Polytechnic University)
Borowska-Stefańska, Marta (Uniwersytet Lodzki)
Wiśniewski, Szymon (Uniwersytet Lodzki)
Dulebenets, Maxim A. (Florida State University)

2023

Time management is crucial for liner shipping services. A variety of unexpected events can disrupt liner shipping schedules. A real-time port capacity analysis and rescheduling the original ship operations would be necessary to counteract the negative effects of such disruptions. Different ship schedule recovery options can be adopted in response to disruptive events (e.g., ship sailing speed adjustment, skipping of disrupted ports). However, shipping lines face conflicting decisions when selecting ship schedule recovery options. As an example, the commonly-used ship speeding-up option could effectively reduce delays during the voyage but would increase the fuel cost. Similarly, the skipping of disrupted ports may substantially decrease the associated delays but would incur additional costs associated with supply chain disruptions and misconnected cargo. Nevertheless, there is a lack of analytical methods that enable the evaluation of competing objectives in ship schedule recovery and effective multi-objective solution approaches. Therefore, this study proposes a novel multi-objective model for ship schedule recovery that aims not only to minimize the total late ship arrivals at ports but also to minimize the total profit loss due to disruptive events that may occur at sea and/or at ports. An epsilon-constraint-based exact optimization algorithm is adopted to obtain optimal Pareto Fronts. The computational experiments conducted for a real-life transit route demonstrate that the adopted exact optimization algorithm is able to generate Pareto Fronts in a timely manner. Moreover, the conducted sensitivity analyses provide interesting insights regarding the effects of different disruption types and unit fuel costs on ship schedule recovery.

Disruptions
Maritime supply chains
Multi-objective optimization
Service reliability
Ship schedule recovery
Uncertainty

http://resolver.tudelft.nl/uuid:9142eda2-7b5d-47b0-a997-0e946848ad18

https://doi.org/10.1016/j.cie.2023.109472

2024-02-05

0360-8352

Computers & Industrial Engineering, 183

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Institutional Repository

journal article

© 2023 Zeinab Elmi, Bokang Li, Benbu Liang, Yui yip Lau, Marta Borowska-Stefańska, Szymon Wiśniewski, Maxim A. Dulebenets