Bunker Cost Research Articles

ECONOMIC BENEFITS OF DEPLOYING FOLDABLE CONTAINERS: REDUCING BUNKER AND CONTAINER MANAGEMENT COSTS IN A MULTI-PORT SHIPPING NETWORK

This study seeks to explore the effectiveness of employing foldable containers (FLDs) in liner shipping to reduce relocation and the empty containers and bunker costs (BCs) associated with ship operations. This resolves a minimum-cost multi-commodity network flow problem by optimizing container fleet size and empty container relocation in a multi-port shipping service network. Port handling time and sailing speed provided by obtained optimal solutions enable the determination of ship BCs as a secondary step. The numerical experiments demonstrate the comparative effect of FLDs against standard ones on the reduction of the costs of empty containers and containership bunker oil.

Route Optimization of Grain Fleet Considering Bunker Cost

To minimize grain fleet operational costs, we employ a route optimization approach that considers bunker costs. A mixed-integer programming model is created, factoring in the unique features of bulk grain shipping and varying oil prices at bunker ports. The goal is to optimize the fleet’s transportation route, with decision variables encompassing bunker port selection, bunker volume, and ship navigation path. Using a dry bulk cargo company’s grain transport fleet as a case study, the Gurobi solver validates the model’s effectiveness. Results reveal that, excluding the loading port, the grain fleet can select low oil price ports along the route for bunkering. Optimal cost reduction is achieved by choosing multiple bunker ports and increasing bunker quantity. Additionally, the model harmonizes port charges with bunker costs, refining the grain fleet’s transportation route and effectively managing operational expenses.

Exploring Drivers Shaping the Choice of Alternative-Fueled New Vessels

The urgent imperative for maritime decarbonization has driven shipowners to embrace alternative marine fuels. Using a robust orderbook dataset spanning from January 2020 to July 2023 (encompassing 4712 vessels, 281 shipyards, and 967 shipping companies), four distinct multinomial logit models were developed. These models, comprising a full-sample model and specialized ones for container vessels, dry bulk carriers, and tankers, aim to identify the key determinants influencing shipowners’ choices of alternative fuels when ordering new vessels. It is interesting to find that alternative fuels (e.g., liquefied natural gas) are the most attractive choice for gas ships and ro-ro carriers; others prefer to use conventional fuels. Furthermore, this study reveals that shipowners’ choices of new fuels significantly correlate with their nationality. While it is well-established that economic factors influence shipowners’ choices for new ship fuel solutions, the impacts of bunker costs, freight rates, and CO2 emission allowance prices remain relatively limited. It is evident that the policies of the International Maritime Organization (IMO) to reduce carbon emissions have increased the demand for building new energy ships. This research contributes to bridging research gaps by shedding light on the intricate interplay of factors that influence shipowners’ preferences for alternative marine fuels amidst global regulatory shifts. It also offers valuable insights for policymakers aiming to incentivize shipowners to transition towards sustainable energy sources.

Optimal scheduling of vessels passing a waterway bottleneck

We develop a novel schedule optimization model for vessels passing a waterway bottleneck. From the system-optimal perspective, the model aims to minimize the total vessel bunker cost and delay penalties at destinations by incorporating the nonlinear relationship between bunker consumption and sailing speed into its calculations. The nonlinear model is linearized via two commonly used approximation techniques. The first one linearizes the bunker consumption function using a piecewise linear lower bound, while the second does so by discretizing the time. Numerical case studies are conducted for a real-world waterway bottleneck, the Three Gorges Dam Lock. Results reveal how the optimal cost components, vessel schedules, and delays are affected by key operating parameters, including the fuel prices, delay penalty rates, and the tightness of sailing time windows. Comparison against two simpler benchmark scheduling strategies (one with no vessel coordination and the other adopting a naïve coordination) manifests the sizeable benefit of optimal vessel scheduling.This paper presents the first investigation into the system-optimal scheduling strategy for vessels navigating a shared bottleneck, considering bunker costs, schedule delay penalties, and varying sailing speeds. The results highlight the significant potential of system-optimal scheduling and potential coordination strategies that enable approximation of the system-optimal solution. Additionally, our numerical experiments uncover the limitations of the outer-approximation method, while demonstrating that the discrete-time approach surpasses it in terms of both solution quality and computational efficiency.

Joint Maritime Bunker Hedging and Operational Consumption Based on CVaR Optimization

Maritime shipping is an important driver of global economic growth. Efficient green maritime technologies are critical for both the profitability and sustainability of shipping carriers due to the fact that fuel consumption has already made up 45–55% of the total operational cost of a ship. Moreover, the application of green maritime technologies also challenges the input/output of the maritime industry. Currently, there is a lack of coordination between the two strategies of maritime bunker management: one is the bunker procurement, which is faced with the fierce volatility of bunker fuel prices, and the other is the bunker consumption of vessel operation scheduling with applicable maritime technologies. To address the challenge posed by the new sulfur emission regulations, the two isolated strategies are inefficient. This study presents an integrated model that takes both the financial technology (bunker hedging) and the operational bunker cost efficiency (sailing speed and routing optimization under emission regulations) into account. The objective is to maximize the total rate of portfolio return considering the revenue and the cost simultaneously. By analyzing the Conditional Value at Risk (CVaR) risk measure, we examined the effects of the bunker spot, contract, and hedging in futures markets on the optimal joint solution. Numerical results from a real-world case study show that the optimized integrating financial and operational strategies yield the lowest expected total costs as well as the highest revenue with CVaR constraints. The findings provide a prospect for maritime shipping as an effective decision tool for bunker management under environmental regulations. The management insights of our study will benefit the corporate participants, policy makers, and researchers in liner shipping revenue and risk management.

Analysis of Slow Steaming of Ship and Its Impacts

Global trade heavily depends on shipping industry. Growth in seaborne trade causes the increase in fuel consumption and hence higher emissions which are directly related to the issues of global warming. Now, the world is also facing a drastic increase in fuel prices as a consequence of geopolitical conflict between Russia and Ukraine. One of the most effective ways to solve these problems in the maritime industry is to use the slow steaming method which is very cost-effective to implement. Slow steaming involves purposefully lowering ship speed to reduce bunker fuel consumption and also results in lower emissions. Therefore, this method is expected to bring a win-win outcome in the face of environmental damage resulted from GHG emissions and soaring fuel prices. This paper seeks to ascertain whether slow steaming can be used to compensate for the higher expenses associated with using cleaner fuels to comply with the stricter environmental regulations set out by International Maritime Organization. The impacts of using this method were evaluated by three points of view – economic, technical and legal. The results show that slow steaming can reduce the increasing bunker cost for using MGO instead of HFO but still cannot fully compensate for it.

Insights on the introduction of autonomous vessels to liner shipping networks

This article investigates economic and operational effects of introducing autonomous vessels to liner shipping networks. By the formulation of optimization models, we analyze how fleet configurations with vessels of different capacity affect the cost and service level of liner shipping networks in both static and dynamic settings. We implement the model in a data instance that extends a data instance on the Baltic trade from conventional to autonomous vessels. Our results show that the introduction of autonomous vessels might lead to cost savings of 7.1% with respect to the fleet of conventional vessels. The main savings come from lower time charter costs and lower bunker costs. The results also suggest that a fleet configuration combining large with small vessels perform better, because of its better ability to accommodate to the asymmetry of the trade. The implementation of a flexible sailing schedule in the dynamic setting might lead to a great increase in the service level of the network, but at the expense of an increase in costs.

Investigating the determinants of shipowners’ emission abatement solutions for newbuilding vessels

• We identify the determinants of the owners’ abatement choice for newbuilding ships. • Vessel type plays a critical role in the shipowners’ abatement solutions. • The shipowners from different countries exhibit a unique abatement preference. • The Sulfur Cap has triggered demand for scrubber but not alternative fuel. • The influence of bunker cost for abatement solutions of new vessels is pretty weak. Because of the long lifetime of newbuilding vessels, shipowners' emission abatement solutions will have a profound impact on the greening transition of the shipping industry. A multinominal logit model is developed to identify the key determinants that affect the shipowners' choice of the solutions. New findings include: (1) Alternative fuels (e.g. liquefied natural gas) are the most attractive choice for gas ships and pure car carriers; and dry bulk ships and crude tankers prefer to use low-sulfur fuels. (2) Singaporean and Japanese shipowners are more likely to adopt the alternative fuels. (3) The IMO 2020 cap has significantly affected shipowners’ preference for scrubbers but not for alternative fuels. It is well known that economic factors affecting a shipowner’s decisions include freight rate and bunker cost but these factors weakly influence the emission abatement solution choice for new ships. This research provides helpful insights for the policymaker to guide shipowners to invest in more eco-friendly vessels and assist various stakeholders in forming efficient decisions.

Estimating a global demand model for soybean traffic through the Panama Canal

This study attempts to fit a global demand model for soybean traffic through the Panama Canal using Ordinary Least Square. Most of the soybean cargo through the interoceanic waterway is loaded on the U.S. Gulf and East Coast ports -mainly destined to East Asia, especially China-, and represented about 34% of total Panama Canal grain traffic between fiscal years 2010–19. To estimate the global demand model for soybean traffic, we are considering explanatory variables such as effective toll rates through the Panama Canal, U.S. Gulf- Asia and U.S. Pacific Northwest- Asia freight rates, Baltic Dry Index, bunker costs, soybean export inspections from the U.S. Gulf and Pacific Northwest, U.S. Gulf soybean basis levels, Brazil’s soybean exports and average U.S. dollar index. As part of the research, we are pursuing the estimation of the toll rate elasticity of vessels transporting soybeans via the Panama Canal. Data come mostly from several U.S. Department of Agriculture sources, Brazil’s Secretariat of Foreign Trade (SECEX) and from Panama Canal transit information. Finally, after estimation of the global demand model for soybean traffic, we will discuss the implications for future soybean traffic through the waterway, evaluating alternative routes and sources for this trade.

Financial and Economic Indicators of Shipping Companies in 2010-2019 Years

Financial and Economic analysis of shipping companies conducted based on main maritime industry segments - Crude Oil, Products, Liquefied Natural Gas (LNG), Dry bulk commodities and Container cargo. Each of them is represented as one or several companies, which are the leaders in these business sectors. The revenues of shipping companies specialized in crude oil and product transportation have been increased significantly in 2010-2019 years, which was a result of increasing ship quantities and tonnage as well as income from time-charter. Stability can be seen in the revenues of liquefied natural gas shipping companies. The growth rate of container shipping company income was comparatively low. Moreover, the share of voyage costs have been increased in bulk commodities transportation in 2010-2019 (From 8% to 25%), decreased operating expenses, amortization of assets, charter and general costs. In the cost structure of liner shipping companies’ transportation and terminal expenses have been increased (From 10% to 26%), while the share of fuel, charter and logistics costs have been decreased. The high and stable profitability incurred in liquified natural gas transportation field as well as in oil shipping transporation with modern, new and large size oil tankers. The dry bulk and liner shipping companies were characterized with sharp unsteadiness and comperatively low profitability. The crude oil and product shipping companies had positive financial results in 2014-2016 and 2019 years, in other years they reported loss. The liquified natural gas transportation companies had a stable profit. Within the same period, dry bulk shipping companies were characterized with the lower or even unprofitability. Container shipping companies had unsteady financial results, in particular their net profit was peaking in 2010, 2014 and 2018 years and ended up with loss in 2011 and 2016 years. Keywords: The revenues of shipping companies, voyage costs, operational costs, charter costs, bunker costs, terminal costs, intermodal costs, port costs.

Shipping Bunker Cost Risk Assessment and Management during the Coronavirus Oil Shock

This research explores ways to develop a risk management strategy that enables shipping companies to reduce unnecessary fuel cost risks, fuel price fluctuations and improve financial management. Through the Monte Carlo method, the study makes use of the simulation of the conditional value-at-risk (CVaR) model. First, the VaR of various shipping-fuel-cost combination over a ten-year period is simulated. Then, through the most appropriate probability distribution test, it is found that most of the VaR of shipping fuel cost combination are in Beta–Arcsine distribution. In other words, the high-frequency data are concentrated at both tails (minimum and maximum) with high volatility. Therefore, the best strategy is to install scrubbers on existing ships to purify their exhaust gas and choose natural gas-based marine fuel for new ships. This will benefit the shipping companies significantly more compared to the use of low-sulfur fuel and choosing forward bunker agreements. Bunker swaps and options of bunker prices to hedging the risk of bunker cost raised in the end of Coronavirus oil shock, the strategy could help achieve the goal of risk management in the sustainable supply chain.

Best maritime transportation option for the Arctic crude oil: A profit decision model

Navigation via the Northern Sea Route (NSR) requires specific vessels in comparison with the Suez Canal Route (SCR). We develop a profit decision model that defines the best option mixing the shipping lane (NSR or SCR) and the ice-class of the vessel (1A, 1AS, and Open Water (OW)) for oil producers operating in the Russian Arctic zone. The effects of the Brent barrel price, bunker cost and ice-thickness are analyzed. The best option depends in fact on the strategy implemented by the shipper. For instance, the solutions of a profit focused strategy or of a cost-oriented strategy are different.

A destination choice model for very large gas carriers (VLGC) loading from the US Gulf

Abstract This study is one of the first to model energy shipping destination choice behaviors and identify their associations with various market factors from charterers' perspective. The paper uses very large gas carriers loading from the US Gulf as an illustration. Attributes include freight rate, propane price spread, bunker costs and number of ships in the destination areas. It also identifies the effects of the Panama Canal expansion on destination choices, by dividing sample data into two sub-periods: pre- and post-expansion. Furthermore, both aggregate and disaggregate analysis for different ports are provided. This work draws significant implications for energy transport planning. Understanding the charterer's choice of destinations is vital in determining traffic flow to a specific destination and in forecasting supply patterns. This model can be applied to other downstream commodity shipping segments with available arbitrage opportunities, less sticky trade flows and active traders.

Impact analysis of the traffic convoy system and toll pricing policy of the Suez Canal on the operations of a liner containership over a long-haul voyage

This paper takes an initiative to quantitatively assess the impact of the traffic control scheme and the stepwise toll pricing policy of the Suez Canal on the optimal sailing schedule of a liner containership. We develop a mixed-integer nonlinear programming model for the optimal sailing schedule of a containership over a long-haul voyage via Suez. A case study on a 13000-TEU containership running on the LP4 service of APL shows several managerial insights: a) ignoring the traffic control system at Suez in ship speed optimisation may lead to an infeasible sailing schedule, and underestimate the operating cost (even the bunker cost) of a containership on a long-haul voyage via Suez; b) the optimal ship recovery plan in terms of its sailing speeds is mainly determined by the predefined port time windows, delay situation and Suez-clock time, but not pretty much affected by the levels of bunker price and transit due.

Impact analysis of the traffic convoy system and toll pricing policy of the Suez Canal on the operations of a liner containership over a long-haul voyage

This paper takes an initiative to quantitatively assess the impact of the traffic control scheme and the stepwise toll pricing policy of the Suez Canal on the optimal sailing schedule of a liner containership. We develop a mixed-integer nonlinear programming model for the optimal sailing schedule of a containership over a long-haul voyage via Suez. A case study on a 13000-TEU containership running on the LP4 service of APL shows several managerial insights: a) ignoring the traffic control system at Suez in ship speed optimisation may lead to an infeasible sailing schedule, and underestimate the operating cost (even the bunker cost) of a containership on a long-haul voyage via Suez; b) the optimal ship recovery plan in terms of its sailing speeds is mainly determined by the predefined port time windows, delay situation and Suez-clock time, but not pretty much affected by the levels of bunker price and transit due.

Impacts of vessel speed on bunker cost in short sea shipping: A cross-examination

Air emissions of shipping have decreased in SECA regions after 2015. Environmental impacts of regulation policies are identifiable and measurable, as a study from the port of Gothenburg recently exposed. In addition to emissions, it is important to understand how regulations and decisions, focusing on environmental sustainability, impact on the maritime business indicators such as transport costs and marginal revenues. When SECA decision was made, the oil and bunker prices were historically high. Prices were also highly volatile. Numerous studies estimated difficulties for shipping companies, and maritime transport dependent export companies. The oil price dropped dramatically in 2016 remaining at the same level till the early 2018. This empirical case study examines and simulates bunker price data in relation to different vessel speeds. The paper looks at how different speed and oil price combinations impact transport costs and export business. The results of this simulation can be summarized with the notion that the negative economic impacts of the oil price variation can be mitigated to some extent by using lower vessel speeds, thus slow steaming, on short sea shipping (SSS). However, variable relations are not straightforward and they require additional studies.

Selection of the most practical Malaysian port for enhancing the Malaysia-China Kuantan Industrial Park business trade

The objective of this paper is to demonstrate the methodology for the selection of the most practical Malaysian port for enhancing the Malaysia-China Kuantan Industrial Park (MCKIP) business trade. A selection is conducted using a combination decision-making method of analytical hierarchy process and evidential reasoning methods by considering five criteria namely: 1) distance; 2) journey time; 3) bunker cost; 4) port facilities; 5) distribution centre. A case study is constructed accordingly, whereby Shanghai Port has selected as a main port in China and four alternatives Malaysian ports namely: 1) Kuantan Port; 2) Johor Port; 3) Port Tanjung Pelepas; 4) Port Klang will be examined. The result shows that Kuantan Port is the most practical port for enhancing the MCKIP business trade compared to others hub ports in Malaysia. It is capable of helping China shipping liners enjoys the high cost saving for cargoes loading and discharging processes.

The Vessel Scheduling Problem in a Liner Shipping Route with Heterogeneous Fleet

Increasing volumes of the international seaborne trade force liner shipping companies to improve efficiency of their operations to remain competitive. Many of liner shipping companies continue increasing size of their vessels, as larger vessels provide lower voyage costs per container due to their economies of scale. Larger vessels also allow liner shipping companies more efficiently share the demand with the alliance partners. Nowadays, many of liner shipping routes are served by vessels of different types (e.g., small, medium, large). However, the key assumption of studies on vessel scheduling, conducted to date, is homogeneous nature of the vessel fleet (i.e., all vessels in the fleet, serving a given liner shipping route, have the same technical characteristics). This study proposes a novel mathematical model for the vessel scheduling problem with heterogeneous fleet. The objective of a mixed integer non-linear model is to minimize the total vessel turnaround cost. Due to high non-linearity of the proposed mathematical model a non-linear optimization solver is used to solve it. Numerical experiments are performed to evaluate efficiency of the proposed solution approach and the novel methodology. Results demonstrate a computational efficiency of the adopted solution approach. Furthermore, vessel schedules are found to be more sensitive to introduction of larger vessels in the fleet as compared to increase in the unit bunker cost.

The Impact of Bunker Risk Management on CO2 Emissions in Maritime Transportation Under ECA Regulation

The shipping industry carries over 90% of the world’s trade, and is hence a major contributor to CO2 and other airborne emissions. As a global effort to reduce air pollution from ships, the implementation of the ECA (Emission Control Areas) regulations has given rise to the wide usage of cleaner fuels. This has led to an increased emphasis on the management and risk control of maritime bunker costs for many shipping companies. In this paper, we provide a novel view on the relationship between bunker risk management and CO2 emissions. In particular, we investigate how different actions taken in bunker risk management, based on different risk aversions and fuel hedging strategies, impact a shipping company’s CO2 emissions. We use a stochastic programming model and perform various comparison tests in a case study based on a major liner company. Our results show that a shipping company’s risk attitude on bunker costs has impacts on its CO2 emissions. We also demonstrate that, by properly designing its hedging strategies, a shipping company can sometimes achieve noticeable CO2 reduction with little financial sacrifice.

Models on ship scheduling in transshipment hubs with considering bunker cost

This paper studies a decision problem for scheduling ships׳ starting operation time in a transshipment hub with considering the bunker cost and the transshipment cost of containers. Based on the information about the handing capacity of the container port in each period, the port operator makes a proper decision and informs the shipping companies about the start operation days of each liner route. The optimized decision may help shipping companies significantly reduce the cost. This study proposes a mixed integer programming model. The NP-hardness of the problem is proved. A local branching based solution method is also developed for solving the model. Extensive numerical experiments demonstrate the optimality of the solution by the proposed method is less than 3% for large-scale problem instances.