2012
DOI: 10.1016/j.trd.2011.10.001
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An epsilon-optimal algorithm considering greenhouse gas emissions for the management of a ship’s bunker fuel

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Cited by 59 publications
(33 citation statements)
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“…Leading shipping companies, therefore, attempt to respond to these environmental challenges. Numerous studies were conducted to suggest ways on how to mitigate the GHG emission [5,9,21]. However, very few studies in the literature attempt to identify the significant factors that motivate shipping firms to adopt GSP, except Lai et al [4].…”
Section: Drivers Influencing the Adoption Of Gspmentioning
confidence: 99%
See 1 more Smart Citation
“…Leading shipping companies, therefore, attempt to respond to these environmental challenges. Numerous studies were conducted to suggest ways on how to mitigate the GHG emission [5,9,21]. However, very few studies in the literature attempt to identify the significant factors that motivate shipping firms to adopt GSP, except Lai et al [4].…”
Section: Drivers Influencing the Adoption Of Gspmentioning
confidence: 99%
“…Therefore, adoption of green shipping practices (GSP) is increasingly popularized by shipping companies [1][2][3]. To address the environmental issues of shipping industry, several researchers have conducted studies on improving and understanding the environmental aspects of the shipping industry [4][5][6][7][8][9]. A literature review on environmental sustainability in shipping [10] showed that increasing studies have been conducted in the last decade, whereas almost no studies existed prior to 2005.…”
Section: Introductionmentioning
confidence: 99%
“…The problem of speed optimization has been considered together with bunkering decisions in Yao et al (2012) and extended to the stochastic case through a scenario-based approach in Sheng et al (2014) and stochastic Kriging-based optimization in Quan et al (2013). Kim et al (2012) explicitly consider the emission aspect.…”
Section: Optimizing Maritime Logistics Via Simulationmentioning
confidence: 99%
“…This gives an advantage in bunker purchasing, when a vessel has a stable schedule known for some months ahead. The regularity in the vessel schedules in liner shipping allows for detailed planning of a specific vessel, as considered in the works of Plum and Jensen (2007), Besbes and Savin (2009), Kim et al (2012), Kim (2014), Sheng et al (2014) and Yao et al (2012). These papers consider variants of a bunker optimization problem considering a single vessel.…”
Section: Literaturementioning
confidence: 99%
“…Yao et al (2012) does not consider stochastic elements nor tanks, but has vessel speed as an variable of the model. The work of Kim et al (2012) minimizes bunker costs as well as startup costs and inventory costs for a single liner shipping vessel. This is done by choosing bunker ports and bunker volumes but also having vessel roundtrip speed (and thus the number of vessels on the service) as an variable of the model; Kim (2014) presents a different algorithm for a similar problem scoping.…”
Section: Literaturementioning
confidence: 99%