Ship Deployment Research Articles

Decarbonizing the inland container fleet with carbon cap-and-trade scheme

Market-based measures, like the carbon cap-and-trade (CCT) scheme, can effectively reduce emissions and promote green technology by internalizing the external costs in the shipping industry. Under the CCT scheme, the government sets the quantity commitment of carbon emissions for a unit of shipping work, and the excessive quantity must be traded from the inner shipping market. To cope with carbon regulation, carriers can adjust their ship deployment plan and adopt new engine technologies to support low-carbon fuels. This paper proposes a bi-level programming model to investigate the effects of the CCT scheme on the decisions of carriers in a competitive inland container shipping network. At the upper level, carriers adjust their own ship deployment plan and the choice of technology and fuel type. At the lower level, the shippers between different origins and destinations choose the shipping lines with the given ship deployment plans of carriers. Two kinds of equilibrium are considered in the proposed problem: the competitive equilibrium of carriers on freight shipment in the inland shipping network and the trading equilibrium of carbon quotas. The former equilibrium can be captured by a traffic assignment model in a similar transit transportation network, and the latter equilibrium follows the idea of the demand–supply equilibrium of carbon quotas in the traditional market. The two equilibria interact since the freight distribution affects the shipping revenue of each ship and the trading equilibrium is related to the total cost of the ship. The properties of the optimal choice of technology and fuel type are theoretically studied. We find that the optimal choice of fuel technology for each ship assigned to any shipping line at any given CCT must be Pareto optimal in the sense of cost-related and emission-relative measures. Based on the result, the optimal solution of the proposed model can be calculated by a sampling-based method. Numerical examples based on the Yangtze River are further adopted to illustrate the proposed model and conclusions.

Ship deployment problem with green technology adoption for an inland river carrier under non-identical streamflow and speed limits

The maritime industry is currently experiencing a shift towards green corridors. The inland waterway is the main transportation corridor with a relatively low adoption of green technologies, which produces heavy air pollution in inland cities. This paper investigates the ship deployment problem for an inland river carrier considering the adoption of green fuel and green technologies for a given ship fleet. A non-linear programming (NLP) model is proposed to jointly optimize green technology adoption, sailing speed, and routing problems while considering two unique characteristics of inland river shipping, including the non-identical streamflow and the speed limits on each shipping leg. The analytical propositions reveal the optimal operation strategy of the inland river ship fleet, and a column generation-based algorithm is further designed to solve the proposed model. By jointly investigating the ship operation strategy and sulphur emissions, we find the following management insights: Firstly, the ship would have a lower willingness to invest in shore power (scrubber) if it installed scrubber (shore power). The higher streamflow and looser speed limits would reduce the spillover effect of green technology adoption. Secondly, emissions will spillover from ports to river legs if only shore power is provided. Our findings provide valuable insights for policymakers to promote complete green technology adoption to achieve comprehensive abatement of the entire inland river.

A two-step approach for deploying heterogeneous vessels and designing reliable schedule in liner shipping services

Schedule reliability is a crucial metric for measuring liner container shipping service. Due to the inherent uncertainties at sea and ports, schedule delays and unreliable on-time performance have long plagued shipping companies. In practice, the heterogeneity of container vessels also creates challenges for deployment and schedule optimization. To address the problem, we develop a two-step approach with two programming sub-models. In the first step, we tackle the challenges of ship deployment and scheduling by considering heterogeneous vessels and capturing the interarrival time between adjacent ports of call. In the second step, we use the conditional value-at-risk (CVaR) to address the uncertainty risk avoidance in schedule design. To solve the stochastic programming models, we employ a solution framework based on the outer linear approximation method and the risk measure method, where CVaR is specified as the risk measure. We illustrate the application of our model on a case study concerning a real route operated by COSCO Shipping Lines. The results show that the total cost of liner shipping service with heterogeneous fleet on the route can be reduce by 4.77% compared with homogeneous fleet. And the cost of risk with the reliable schedule can be decreased by 8.04% compared with the ideal schedule. The research conclusions can provide some useful decision-making references for shipping companies to deploy heterogeneous vessels and design reliable schedules.

Vulnerability analysis of cruise shipping in ASEAN countries facing COVID-19 pandemic

The COVID-19 pandemic has significantly affected the cruise shipping industry, disrupting ports and shipping. However, current research predominantly focuses on the impact on individual ports or vessels, leaving a gap in understanding how these disruptions propagate across cruise shipping networks. To address this gap, a novel vulnerability assessment methodology that offers a comprehensive perspective on the broader impact of COVID-19 on cruise shipping networks is developed. It first uses a new weight social network analysis approach to quantify the vulnerability of each cruise port in a shipping network and then combines the curie port local pandemic risk to generate a new index to reveal the COVID-19 impact on the whole cruise shipping network systematically. The new methodology is applied to analyse the ASEAN cruise shipping network. This real-world COVID-19 pandemic case study yields valuable insights that bridge theoretical and practical domains. Integrating local port-level vulnerabilities with shipping network-level vulnerabilities creates a unique index. This index quantifies the individual and collective influence of COVID-19 risks at different cruise ports on the entire regional cruise shipping network. The results directly impact cruise lines seeking to enhance their operations' resilience in the face of COVID-19 challenges. The vulnerability index explains how risk exposure at various ports shapes the network's dynamics. This insight empowers cruise lines to optimise ship deployment schedules, lowering the network's overall COVID-19 pandemic risk. The research method and outcomes offer a pioneering perspective on the vulnerability of cruise shipping networks to COVID-19 disruptions, and other possible disruptions (e.g., climate change) in a broad sense. By elucidating interconnected vulnerabilities, cruise lines are equipped with actionable insights to navigate the complexities of global challenges.

Probabilistic operability and greenhouse gas assessment during dynamic positioning operations

A Dynamic Positioning system automatically maintains both the position and heading of a vessel by using its thrusters in the presence of external disturbances. This goal is ensured by a controller that compensates for the environmental disturbances and computes the proper set-points for each actuator. The core of such a system is composed of force and thrust allocation modules that tailor the required forces and moment over the available actuators. The propulsion systems used are often over-actuated and the thrust allocation algorithm implies an infinite number of solutions since it is impossible to solve analytically the problem. Over the years efforts from the research community dealt with the optimization in terms of accuracy, energy consumption, and maintenance with innovative allocation strategies were investigated. However, no publications or rules indicate the procedure for the evaluation of exhaust gas emission during dynamic positioning operations. For such a reason, the paper aims to develop an optimization procedure that includes an ad-hoc objective function with relative non-linear constraints for the thrust allocation logic that tends to minimize the actuators’ thrust. The procedure accounts for non-linear hydrodynamic effects on the thrust generation, including thruster-thruster and thruster-hull interactions, to obtain the most realistic results as possible. Moreover, following the IMO suggestions, the production of greenhouses gases emissions is evaluated in probabilistic terms. The proposed approach provides indicators in terms of yearly operability, fuel consumption, and environmental footprint during dynamic positioning operations that could be used for proper decisions in ship deployment.

Optimal Ship Deployment and Sailing Speed under Alternative Fuels

The European Union (EU) has implemented a sub-quota of 2% for renewable marine fuels to be utilized by vessels operating within its jurisdiction, effective starting from 2034. This progressive policy signifies a significant leap towards reducing carbon emissions and promoting sustainable development. However, it also presents notable challenges for shipping companies, particularly in terms of fuel costs. In order to support shipping companies in devising optimal strategies within the framework of this new policy, this study proposes a mixed-integer linear programming model. This model aims to determine the optimal decisions for fuel choice, sailing speed and the number of vessels on various routes. Furthermore, we showcase the adaptability of our model in response to fluctuations in fuel prices, relevant vessel costs, and the total fleet size of vessels. Through its innovative insights, this research provides invaluable guidance for optimal decision-making processes within shipping companies operating under the new EU policy, enabling them to minimize their total costs effectively.

Seasonality of the global cruise industry

Seasonality is a unique characteristic of the cruise industry. Cruise lines move their ship deployment areas seasonally to meet tourism needs. Taking advantage of the climatic differences between the Northern and Southern Hemispheres could allow greater growth in the global cruise industry. This study aims to provide basic findings for governments and ports to consider ways to encourage growth by capitalizing on the seasonality of the global cruise industry. Automatic identification system data for all ocean-going cruise ships worldwide in 2019 were compiled and categorized into three travel groups (short, middle, and long) based on the latitudinal distance traveled. Differences between these three groups were analyzed in terms of deployment area/port, vessel size, and itinerary design. As a result, we found that the long travel group had the following characteristics. Cruise ships were deployed to Alaska and Northern Europe in summer and dispersed to the equator and Southern Hemisphere in winter. The vessel size was standard and neither too large nor too small. Specifically, long travel of cruise ships was limited by the maximum gross tonnage, length, and breadth of the ship, but there was no draught restriction. Although the number of nodes and edges, and the average degree comprising the itineraries were high, hub ports appeared only in the summer. Furthermore, despite the long distances traveled by season, the number of communities tended to be small, reflecting the design of their itineraries. In conclusion, the development of several ports in the Southern Hemisphere that can accommodate mega-sized cruise ships with standard draught, while considering overtourism, would allow cruise ships to take advantage of the seasonality and, thereby, grow the cruise industry.

Analysis of fleet deployment in the international container shipping market using simultaneous equations modelling

ABSTRACT The shipping industry is a capital-intensive industry in which ship investment and demolition are directly related to the company’s profitability, transportation capacity, and fleet structure. Thus, companies need to consider investment and demolition activities carefully before making decisions about fleet deployment. This study focuses on decisions related to investment in new and second-hand vessels as well as vessel demolition in different sub-markets of the container shipping market at the same time. By considering market factors, operating conditions, and shipping alliances, we developed a systematic model for the container market. This model innovatively employs a simultaneous equations model (SEM) to analyze fleet deployment decisions and uses the three-stage least squares method to avoid endogenous effects. The results indicate that shipping alliances, fleet deployment, and bunker price all have significant effects on the investment and demolition decisions of shipping companies. We further discuss the strategic decisions of shipping companies related to joining shipping alliances and highlight the considerations of larger companies when expanding (primarily squeezing out competition and responding to the market). The results provide valuable information for shipping companies to determine the best ship deployment strategies and avoid overcapacity.

How to Deploy Electric Ships for Green Shipping

Maritime transport plays an important role in global economic development but also inevitably faces increasing pressures from all sides, such as ship operating cost reduction and environmental protection. An ideal innovation to address these pressures is electric ships, which are more environmentally friendly than conventional manned fuel oil ships. The electric ship is in its early stages. To provide high-quality transportation services, the service network needs to be designed carefully. Therefore, this research simultaneously studies the location of charging stations, charging plans, route planning, ship scheduling, and ship deployment under service time requirements. The problem is formulated as a mixed-integer linear programming model with the objective of minimizing total cost comprised of charging cost, construction cost of charging stations, and fixed cost of ships. A case study using the data of the shipping network along the Yangtze River is conducted in order to evaluate the performance of the model. Valuable managerial insights are also derived from sensitivity analyses.

Shipping network optimization of port equipment components based on improved genetic algorithm

The management of components ensures that the port equipment is in good working condition, ensure port production safety and continuity. In this paper, a port equipment component supply network optimization model that considers the characteristics of shipping network is proposed to optimize hub port selection, route choice, ship deployment, inventory optimization, etc. At the same time, an improved genetic algorithm is developed, including chromosome matrix, row column crossover genetic operation, and double-layer parallel search. The results show that the model and algorithm can effectively obtain a better solution and achieve the optimization goal.

HANDLING TEMPORAL COMPLEXITY IN THE DESIGN OF NON-TRANSPORT SHIPS USING EPOCH-ERA ANALYSIS

A core aspect of temporal complexity in the design of non-transport vessels is the uncertainty related to the future market and contract opportunities, and the corresponding changeability that should be incorporated into the ship design to meet this uncertainty. The development of an appropriate design specification for a new ship represents a core strategic decision for ship owners as part of a fleet renewal or expansion programme, with a high financial risk and a long time horizon of typically 20-30 years. This type of temporal complexity is one out of several complexity aspects to be handled as part of a ship design process.
 In this paper we model possible realizations of an uncertain future for a vessel using the Epoch-Era Analysis (EEA) method. Here, we use the epochs as the primary instrument for capturing major market developments, such as the opening of new offshore areas, new emission regulatory regimes, or the availability of new, disruptive technologies. From these, more specific epoch variables are derived, for which specific contract opportunities can be generated. The epoch-specific performance of the vessels is found by solving a Ship Design and Deployment Problem (SDDP) of concurrently identifying both a preferable ship design and the corresponding path of consecutive contracts that maximizes total revenue.
 We present a case study related to the design of an Anchor Handling Tug Supply (AHTS) vessel. The study illustrates the complexity in striking the correct balance between optimizing the vessel for an initial scenario, while at the same time providing addition performance capabilities to be competitive in the context of future market requirements.

Deploying, scheduling, and sequencing heterogeneous vessels in a liner container shipping route

Previous studies on liner container shipping operations usually assume identical container ships deployed in the same shipping route. However, in real operations, this assumption does not always hold considering the distinct capacities, ages, fuel efficiencies, cost structures, etc. of these ships. These distinctions significantly influence the number of containers transported, the bunker fuel consumption, and the operating cost of a shipping route. In this regard, this paper considers the joint ship deployment, sequencing, and scheduling problem for a fleet of heterogeneous vessels in a shipping route. A mixed integer programming model is developed to select the optimal ships from a set of candidate ships together with their sequences, schedules, and sailing speeds in the shipping route to minimize the total cost. A tailored solution algorithm is subsequently developed to calculate the global optimal solution. Numerical experiments demonstrate that this algorithm significantly outperforms the classical branch-and-cut algorithm in solving the model. In addition, by applying our model in a real-case shipping route, we find that the model is able to reduce the total cost by 5% compared with that considering homogeneous vessels. Finally, several managerial insights are obtained to guide the operations of a liner shipping route.

Cold chain shipping mode choice with environmental and financial perspectives

Mode choice between reefer bulk and container in seaborne cold chains for time sensitive products is a practical problem, in which limited studies are available to guide decision makers. This study thoroughly investigates the cold chain mode choice problem by selecting shipping mode (containerized transport and bulk transport) for each shipment and determining shipment quantities and ship deployment in a multi-period planning environment with independent perishable product demands. Value-Based Management as a novel method in shipping is adopted to consider both economic and environmental objectives from operational and financial aspects. The value-based mode selection models also determine the sailing speed of the heterogeneous chartered reefer bulk fleet under different chartering terms. Furthermore, the paper evaluates greenhouse gas emissions from the cold chain shipping. Findings from a numerical example show that optimal ship speed decreases with a reducing rate when the bunker price increases and with a higher decline rate when goods are less perishable.

Bounds on ship deployment in container shipping with time windows

This paper extends and complements the liner shipping literature by examining the ship deployment decision in the presence of time windows at container ports. A set of tight bounds on the number of ships that can be deployed is derived, revealing a number of fundamental insights into the impact of time windows on ship deployment. The bounds in this paper can also enable the extension of single-route shipping models that have appeared in the literature to the system-wide level by taming the increase in computational requirements.

Fleet deployment and demand fulfillment for container shipping liners

This paper models and solves a fleet deployment and demand fulfillment problem for container shipping liners with consideration of the potential overload risk of containers. Given the stochastic weights of transported containers, chance constraints are embedded in the model at the strategic level. Several realistic limiting factors such as the fleet size and the available berth and yard resources at the ports are also considered. A non-linear mixed integer programming (MIP) model is suggested to optimally determine the transportation demand fulfillment scale for each origin-destination pair, as well as the ship deployment plan along each route, with an objective incorporating revenue, fixed operation cost, fuel consumption cost, holding cost for transhipped containers, and extra berth and yard costs. Two efficient algorithms are then developed to solve the non-linear MIP model for different instance sizes. Numerical experiments based on real-world data are conducted to validate the effectiveness of the model and the algorithms. The results indicate the proposed methodology yields solutions with an optimality gap less than about 0.5%, and can solve realistic instances with 19 ports and four routes within about one hour.

Integrated planning of ship deployment, service schedule and container routing

This paper provides an integrated planning model for container shipping liners. For a shipping network with multiple routes connected by transshipment hubs, the model can simultaneously decide ship deployment along routes, a service schedule including visit times and speed on legs, and cargo allocation to routes for each origin-destination pair. The model considers realistic factors, such as container handling and holding costs at the transshipment hubs, shipping time for each origin-destination pair, penalties for late delivery, ship capacity and speed-dependent fuel costs. Three efficient solution methods are suggested to solve this complex mixed-integer programming model under different scales of problem instances. Computational results based on real data show that the proposed methods cannot only yield solutions with optimality gaps about 0.3% on instances with four routes, but can also solve cases with ten routes and 59 ports in about one and a half hour. This study provides shipping liners with a comprehensive decision tool to make some long-term decisions.

Versatility vs. retrofittability tradeoff in design of non-transport vessels

In this paper, we study the relationship between economic performance and flexibility for non-transport vessels. More specifically, we investigate the difference between two means of achieving flexibility: retrofittability and versatility, i.e., the ability of a vessel to satisfy diverse needs with or without change of physical form, respectively. A model is presented to study this relationship, where we first generate design alternatives with relevant, flexible properties before we subsequently evaluate the design alternatives based on their expected discounted economic lifecycle performance. The evaluation model is based on a two-level decomposition of the planning horizon to handle temporal complexity, using scenario planning and Epoch-Era analysis (EEA) for long-term strategic considerations, and Monte Carlo simulation and optimization for medium-term tactical ship deployment. The proposed model is applied to an offshore construction ship design case. Findings indicate that retrofittability can increase economic performance significantly for non-transport vessels operating in an uncertain heterogeneous context.

Strategies of refueling, sailing speed and ship deployment of containerships in the low-carbon background

Abstract To solve the problems of refueling, ship speed determination and ship deployment of containerships, based on the nonlinear relationship between ship sailing speed, fuel consumption and carbon emissions, a corresponding nonlinear mixed integer programming model is developed by taking container transportation cost, fuel consumption cost and carbon emissions cost in multiple service routes as the total cost objective function, and ship refueling ports, refueling amounts, sailing speed and ship deployment quantities in the route as decision variables. The optimal solution can be obtained by transforming the nonlinear discrete mixed integer programming model into a nonlinear continuous programming model. The proposed model is applied to an Asia-Europe service route of China Shipping (Group) Company. The results show that the optimal refueling policy, speed selection and ship deployment can be determined using the proposed model and solution method. The impact of fuel price, container transportation quantity, ship tanker capacity and carbon tax rate on ship refueling strategy, speed and deployment is investigated. Some insights obtained from example analysis are provided.

A Refueling Scheme Optimization Model for the Voyage Charter with Fuel Price Fluctuation and Ship Deployment Consideration

Abstract Due to the long operation cycle of maritime transportation and frequent fluctuations of the bunker fuel price, the refueling expenditure of a chartered ship at different time or ports of call make significant difference. From the perspective of shipping company, an optimal set of refueling schemes for a ship fleet operating on different voyage charter routes is an important decision. To address this issue, this paper presents an approach to optimize the refueling scheme and the ship deployment simultaneously with considering the trend of fuel price fluctuations. Firstly, an ARMA model is applied to forecast a time serials of the fuel prices. Then a mixed-integer nonlinear programming model is proposed to maximize total operating profit of the shipping company. Finally, a case study on a charter company with three bulk carriers and three voyage charter routes is conducted. The results show that the optimal solution saves the cost of 437,900 USD compared with the traditional refueling scheme, and verify the rationality and validity of the model.

Design of a low-cost oil spill tracking buoy

With the rapid development of offshore oil exploitation, risk of oil spill accidents increases. Environment impact could be reduced if we can locate and forecast the diffusion area of oil slick in real-time for quick accident rescue measurement. We have designed an oil spill tracking buoy (OSTB), which could track oil slick and transfer its latitude and longitude location periodically by Beidou satellite communication system to monitor terminal. Oil slick tracking ability relies on wind/water sail design which based on hydrodynamic equilibrium model and ocean dynamic analysis. Machinery structure is designed for both air deployment and ship deployment. Laboratory test and field experiment in Jiaozhou Bay, Qingdao, China, have proved the spilled oil tracking ability and easy-deployment of the buoy. With novel construction and a total materials cost of about $140USD, this buoy could monitor offshore area oil spill accidents continuously and provide a potential monitor solution for marine activities.