The liner shipping berth scheduling problem with transit times

Reinhardt, Line Blander; Plum, Christian Edinger Munk; Pisinger, David; Sigurd, Mikkel M.; Vial, Guillaume T.P.

doi:10.1016/j.tre.2015.12.006

Cited by 33 publications

(27 citation statements)

References 18 publications

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“…Computational tests show that the potential for reducing fuel consumption, and hence environmental emissions, is substantial. The speed optimization problem presented in Reinhardt et al (2016) determine the sailing speed of the vessel in a leg and affects both the bunker consumption and the duration of the sailing in the leg. Reinhardt et al (2016) solve the liner shipping network optimization, accounting for fuel consumption minimization on the sailing legs through an approximated piecewise linear function for the speed-fuel consumption relationship.…”

Section: Speed Optimization Literaturementioning

confidence: 99%

The multi-port berth allocation problem with speed optimization and emission considerations

Venturini

Iris

Kontovas

et al. 2017

Transportation Research Part D: Transport and Environment

154

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The multi-port berth allocation problem with speed optimization and emission considerations http://researchonline.ljmu.ac.uk/id/eprint/6580/ Article LJMU has developed LJMU Research Online for users to access the research output of the University more effectively. AbstractThe container shipping industry faces many interrelated challenges and opportunities, as its role in the global trading system has become increasingly important over the last decades. On the one side, collaboration between port terminals and shipping liners can lead to costs savings and help achieve a sustainable supply chain, and on the other side, the optimization of operations and sailing times leads to reductions in bunker consumption and, thus, to fuel cost and air emissions reductions. To that effect, there is an increasing need to address the integration opportunities and environmental issues related to container shipping through optimization. This paper focuses on the well known Berth Allocation Problem (BAP), an optimization problem assigning berthing times and positions to vessels in container terminals. We introduce a novel mathematical formulation that extends the classical BAP to cover multiple ports in a shipping network under the assumption of strong cooperation between shipping lines and terminals. Speed is optimized on all sailing legs between ports, demonstrating the effect of speed optimization in reducing the total time of the operation, as well as total fuel consumption and emissions. Furthermore, the model implementation shows that an accurate speed discretization can result in far better economic and environmental results.

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Section: Speed Optimization Literaturementioning

confidence: 99%

The multi-port berth allocation problem with speed optimization and emission considerations

Venturini

Iris

Kontovas

et al. 2017

Transportation Research Part D: Transport and Environment

154

View full text Add to dashboard Cite

show abstract

“…In fact, most liner shipping optimization models that do include ship speed as a decision variable typically do not consider the possible impact of the state of the market on ship speed as being within the scope of their analysis. These include (among others) Alvarez (2009), Brouer et al (2017), Cariou (2011), Doudnikoff and Lacoste (2014), Eefsen and Cerup-Simonsen (2010), Guericke and Tierney (2015), , Lang and Veenstra (2010), Meng and Wang (2011), Notteboom and Vernimmen (2010), Qi and Song (2010), Reinhardt et al (2016), Song et al (2017), Yao et al (2012), and Zis et al (2015). An exception is the recent paper by Xia et al (2015), where a model which incorporates income considerations is presented, even though there is no analysis on the impact of higher or lower freight rates on how fast or slow containerships may go.…”

Section: Introductionmentioning

confidence: 99%

The profit maximizing liner shipping problem with flexible frequencies: logistical and environmental considerations

Giovannini

Psaraftis

2018

Flex Serv Manuf J

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Section: Introductionmentioning

confidence: 94%

“…The basic problem of speed optimization has already been dealt with in Reinhardt et al [28]. Both in the present paper and in the problem solved in [28] the speed optimization is applied to a given network with given cargo routes and transit time requirements. The present paper extends the model presented in [28] to handle a large number of real-life business constraints that are necessary to take into account when optimizing the speed of rotations.…”

Section: Introductionmentioning

confidence: 94%

Speed optimizations for liner networks with business constraints

Reinhardt

Pisinger

Sigurd

et al. 2020

European Journal of Operational Research

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In 2018 the International Maritime Organization (IMO) agreed to cut the shipping sector's overall CO2 output by 50% by 2050. One of the key methods in reaching this goal is to improve operations to limit fuel consumption. However, it is difficult to optimize speed for a complete liner shipping network as routes interact with each other, and several business constraints must be respected. This paper presents a unified model for speed optimization of a liner shipping network, satisfying numerous real-life business constraints. The speed optimization is in this research achieved by rescheduling the port call times of a network, thus, the network is not changed. The business constraints are among others related to transit times, port work shifts and emission control areas. Other restrictions are fixed times for canal crossing, speed restrictions in the piracy areas and desire for robust solutions. Vessel sharing agreements and other collaboration between companies must also be included. The modeling of the different restrictions is described in detail and tested on real-life data. The scientific contribution of this paper is threefold: We present a unified model for speed optimization together with numerous business constraints. We present a general framework for handling routes with different frequencies. Moreover, we present a bi-objective model for balancing robustness of schedules against fuel consumption. The tests show that the real-life requirements can be handled by mixed integer programming and that the model finds significant reductions of bunker consumption and cost for large-scale real-life instances.

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The liner shipping berth scheduling problem with transit times

Cited by 33 publications

References 18 publications

The multi-port berth allocation problem with speed optimization and emission considerations

The multi-port berth allocation problem with speed optimization and emission considerations

The profit maximizing liner shipping problem with flexible frequencies: logistical and environmental considerations

Speed optimizations for liner networks with business constraints

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