Bunker purchasing with contracts

Plum, Christian Edinger Munk; Jensen, Peter Neergaard; Pisinger, David

doi:10.1057/mel.2014.7

Cited by 24 publications

(6 citation statements)

References 21 publications

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“…by the amount of cargo on board. The obtained results are comparable with the results obtained in the case of linear shipping organisation models [1][2][3][4][5][6][7][8][9][10][11][12], based on fuel consumption.…”

Section: Simulation C) Node 1 Has the Worst Evaluation Of All The Othsupporting

confidence: 82%

“…It can also be noted that researchers have paid more attention to the optimal bunkeringrefuelling decision problem than to which factors and characteristics influence the choice of the bunkering port. On the other hand, the majority of the proposed models are based on linear shipping organisation [1][2][3][4][5][6][7][8][9][10][11][12], while researchers have seldom considered hub and spoke [13] or tramp services [14,15].…”

Section: Introductionmentioning

confidence: 99%

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MCDM Bunkering Optimisation in a Hub and Spoke System: The Case of the North Adriatic Ports

Tuljak-Suban

2019

PROMET

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Choosing an optimal bunkering port that minimises the increase in the operating costs in a hub and spoke system is a multi-criteria decision-making (MCDM) problem. Furthermore, the criteria are related to the port particularities, the environment, fuel price, and some criteria are quantitative while others are qualitative. It is therefore necessary to create a model that takes such features into consideration. Firstly, in this paper a set of the most used criteria will be defined. Then, a method to choose suitable criteria for a hub and spoke system will be proposed. Secondly, using a Fuzzy AHP, weights will be defined and used in a multi-criteria goal function. The outcome is a bunkering policy MCDM model based on the aggregation of fuel consumption and price to criteria related to port characteristics, local aspects and service particularities. All these factors must be considered by a chief engineer (superintendent) in the process of defining a sustainable bunker policy. A case study based on the North Adriatic port system demonstrates the applicability of the proposed model. In addition, the case study highlights that in hub and spoke systems with short loops, feeder ships can regulate cargo capacity and stay at a port with bunkering policy planning.

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Section: Simulation C) Node 1 Has the Worst Evaluation Of All The Othsupporting

confidence: 82%

Section: Introductionmentioning

confidence: 99%

MCDM Bunkering Optimisation in a Hub and Spoke System: The Case of the North Adriatic Ports

Tuljak-Suban

2019

PROMET

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“…offered a comprehensive literature review on this topic. Norstad et al (2011), Ronen (2011), Fagerholt et al (2010), Xia et al (2015) and Wang and Meng (2012) focused on sailing speed optimization and fuel cost minimization; Psaraftis and Kontovas (2010) and Lindstad et al (2011) investigated the relationship between slow steaming and fleet size in container shipping; Yao et al (2012), Plum et al (2014) and Wang and Meng (2015) proposed optimization models regarding bunkering port choice. However, most of these papers focus on only one of the two levels.…”

Section: Introductionmentioning

confidence: 99%

Integrated maritime fuel management with stochastic fuel prices and new emission regulations

Wallace

Wang

2018

Journal of the Operational Research Society

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Maritime bunker management (MBM) controls the procurement and consumption of the fuels used on board and therefore manages one of the most important cost drivers in the shipping industry. At the operational level, a shipping company needs to manage its fuel consumption by making optimal routing and speed decisions for each voyage. But since fuel prices are highly volatile, a shipping company sometimes also needs to do tactical fuel hedging in the forward market to control risk and cost volatility. From an operations research perspective, it is customary to think of tactical and operational decisions as tightly linked. However, the existing literature on MBM normally focuses on only one of these two levels, rather than taking an integrated point of view. This is in line with how shipping companies operate; tactical and operational bunker management decisions are made in isolation. We develop a stochastic programming model involving both tactical and operational decisions in MBM in order to minimize the total expected fuel costs, controlled for financial risk, within a planning period. This paper points out that after the latest regulation of the Sulphur Emission Control Areas (SECA) came into force in 2015, an integration of the tactical and operational levels in MBM has become important for shipping companies whose business deals with SECA. The results of the computational study shows isolated decision making on either tactical or operational level in MBM will lead to various problem. Nevertheless, the most server consequence occurs when tactical decisions are made in isolation.

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“…Although bunker price statistics are presented as a net value by some sources, bunkering is a pooled resource. For this reason, discounts can be applied to the prices according to the quantity, or a lower-upper limit can be determined against too volatile prices (Farina et al, 2014). However, we based our study on the prices offered by the source, because otherwise it would be very difficult to apply an analysis in accordance with our methodology.…”

Section: Datamentioning

confidence: 99%

The price behavior of the MGO bunker market: An integrated causality and interpretive structural modeling approach

Açık

2021

Marit. Technol. Res.

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Marine fuel price differences of supply centers have a significant effect on operators’ budgets, and so are closely monitored by traders, charterers and shipowners. The aim of this study is to determine the volatility spillovers between the prices of the major fuel centers in the world and to form a hierarchical structure based on the influence and dependence powers of these centers. For this purpose, an integrated structure of causality in variance and Interpretive Structural Modeling (ISM) methods are used. The data set used in this study includes marine gas oil (MGO) prices for 8 fuel centers used extensively in the world, namely: Fujairah, Hong Kong, Houston, Istanbul, New York, Piraeus, Rotterdam, and Singapore. This data consists of 782 daily observations covering a 3-year-period between 14.04.2017 and 13.04.2020. The ISM results reveal that these fuel centers lie at 6 different levels based on their driving and dependence powers, sources of price volatility in the market are Fujairah and Singapore, and the center that is most affected by volatility is Piraeus. In addition to drawing a macro frame for the fuel market, the results obtained are thought to be useful in reducing risk in the market due to uncertainty for stakeholders.

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Bunker purchasing with contracts

Cited by 24 publications

References 21 publications

MCDM Bunkering Optimisation in a Hub and Spoke System: The Case of the North Adriatic Ports

MCDM Bunkering Optimisation in a Hub and Spoke System: The Case of the North Adriatic Ports

Integrated maritime fuel management with stochastic fuel prices and new emission regulations

The price behavior of the MGO bunker market: An integrated causality and interpretive structural modeling approach

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