Liner Shipping Network Design Research Articles

Approximate dynamic programming for liner shipping network design

AbstractThe global containerised trade heavily relies on liner shipping services, facilitating the worldwide movement of large cargo volumes along fixed routes and schedules. The profitability of shipping companies hinges on how efficiently they design their shipping network; a complex optimization problem known as the liner shipping network design problem (LSNDP). In recent years, approximate dynamic programming (ADP), also known as reinforcement learning, has emerged as a promising approach for large-scale optimisation. This paper introduces a novel Markov decision process for the LSNDP and investigates the potential of ADP. We show that ADP methods based on value iteration produce optimal solutions to small instances, but their scalability is hindered by high memory demands. An ADP method based on a deep neural network requires less memory and successfully obtains feasible solutions. The quality of solutions, however, declines for larger instances, possibly due to the discrete nature of high-dimensional state and action spaces.

Liner shipping network design problem in modern transportation system of Russia

The liner shipping network design problem is considered in the paper. This problem is particularly relevant in the current global political and economic conditions, where finding optimal solutions for business becomes crucial for survival. State-of-the-art formulations and methods for solving the problem in domestic and international scientific papers are discussed. Four types of liner services such as simple service, “butterfly”, “pendulum” and complex service are described. A simple service that can be reduced to the traveling salesman problem is primarily focused on. Our own formulation of the problem is proposed and an example of liner shipping network description, based on the proposed formulation, is provided. In the example, presented in the paper, a container line, based on a single domestic seaport (Vladivostok) and four seaports in China, is demonstrated. It should be noticed, that the problem includes several optimization sub-problems (such as multi-commodity flow problem), solving which is important for finding best solutions for the designed shipping line, but is outside the bounds of this research. The liner services as a sequence of vessel calls to ports are described; and some results of the foregoing generation process are discussed. The optimal solution is selected from the set of generated solutions. It represents a particular case that simultaneously has the lowest costs for implementing the container line and the highest number of serviced container flows. It is noted that this solution is optimal only within the generated solution space and may not be optimal for the considered example of the problem.

Liner shipping network design model with carbon tax, seasonal freight rate fluctuations and empty container relocation

In response to the challenges posed by the shipping carbon tax resulting from the low-carbon environmental policy, the seasonal fluctuation of freight rates in the container liner shipping market, and the reduced flexibility in fleet adjustment, we develop a bi-level programming model to maximize the average revenue per container ship and the total revenue of the fleet.The upper-level model selects the optimal shipping networks for both the off-season and peak season, while also designing the liner fleet for these two networks. The lower-level model optimizes the slot allocation scheme and the empty container storage and transportation scheme to evaluate the revenue of the network calculated by the upper-level model. Three meta-heuristic algorithms are proposed. We take the China-West Europe liner shipping route as the research object, and conduct numerical experiments on different optimization objectives and liner types. Results demonstrate that maximizing the average revenue per container ship involves reducing the carbon tax cost, simplifying the trunk route structure, and increasing the number of feeder routes. These changes lead to reduced satisfaction rates for transportation demands in both China and Europe. If the company seeks to maximize total revenue, they may achieve the opposite result. Therefore, liner companies should reasonably set optimization goals, adjust the network structure and liner operation status in a timely manner, and scientifically allocate container ship and empty containers to achieve the operational goals of reducing carbon emissions and maximizing revenue to cope with the volatile market and the low-carbon regulations.

Bibliometric Review of Route Optimization in Maritime Transportation: Environmental Sustainability and Operational Efficiency

Route optimization in maritime transportation provides enormous cost saving and efficient resource allocation for companies. Shipping companies need to create an optimized route for shipping fleets. That is why route optimization has gained considerable and increasing attention in maritime transportation literature over the past few years. This research aims to identify the theoretical cornerstones, current research trends, and possible research avenues for future studies by reviewing 256 peer-reviewed route optimization articles in maritime transportation literature. For this purpose, first, theoretical cornerstones of route optimization in maritime transportation literature were examined by co-citation analysis and three clusters were identified: fleet routing and deployment; liner shipping rotation; and optimization of fuel consumption and vessel speeds. Second, current research trends of route optimization in maritime transportation literature were uncovered via bibliographic coupling analysis. The analysis results revealed that current research trends could be considered in four clusters: route planning; routing under different weather conditions; liner shipping network and service design; and environmental speed optimization. Finally, author-keyword analysis was performed to specify knowledge gaps and recommend future research areas.

Liner-Shipping Network Design with Emission Control Areas: A Real Case Study

In recent years, liner-shipping companies have faced a traditional trade-off between cost and emission (CO2 and SOX) reduction. This study considers this element to construct a liner-shipping network design model which includes a package-cargo transport plan, route allocation, and route design. The objective is to maximize profit by selecting the ports to be visited, the sequence of port visits, the cargo flows between ports, and the number/operating speeds of vessels. In addition, emission control areas (ECAs) exist in the liner network. With reference to the idea of the column generation algorithm, this study proposed a heuristic algorithm based on empirical data through a real case calculation and selected the optimal scheme, which is in-line with both economic and environmental benefits. The results show that the model and optimization method are feasible and provide an effective solution for the liner network design of shipping companies, while also considering environmental factors. In addition, the effects of the number of ECAs, inter-port origin-destination (OD) demand, freight rate, fuel price, and carbon prices on the design of transport networks are discussed to provide a reference for the operation of shipping companies and government decision-making.

On the liner shipping network design: the Maritime Silk Route case study

The Maritime Silk Route is a crucial channel for economic exchanges between China and Europe. In the year 2018, the sea route between Asia and Europe moved more than 24 million TEU. In this context, the optimal design of liner services is of crucial importance. We present a general framework for the optimal design of these services. First, we develop a gravity model representing the spatial interaction between ports. Then we obtain a minimum spanning tree by means of Kruskal optimisation and finally we use the Louvain method to determine the communities within the network. Two scenarios are discussed. The first gives more importance to distances, while the second gives more importance to port throughputs. The paper discusses the main differences between the two cases and highlights which ports gain or lose connections depending on the market environment. The resulting graphs are a good reference for designing better services.

A branch-and-price algorithm for solving the single-hub feeder network design problem

In liner shipping, containers are generally transshipped in major hub ports in each region, between larger inter-region vessels and smaller feeder vessels. In this paper, we study the problem of designing the feeder vessel network, transporting containers between a regional hub and the surrounding feeder ports. The problem, as modelled, has many similarities with the split delivery vehicle routing problem, but with additional characteristics such as simultaneous pickups and deliveries and weekly departures. The problem also includes fleet sizing with a heterogeneous fleet and allows demand rejection at a penalty cost. We present a branch-and-price framework to solve the problem, where the subproblem is solved by enumerating vessel routes and subsequently assigning commodities by solving a min-cost flow problem for each commodity. The algorithm is tested on instances with up to 12 ports, which are all solved to optimality. Since the problem is similar to the liner shipping network design problem but without transshipments, we further study selected instances from the LINER-LIB instance suite. The Baltic instance is solved to proven optimality and we find the best known solution to the West Africa instance, significantly improving on what can be found in the literature.

Liner shipping network - transaction mechanism joint design model considering carbon tax and liner alliance

As a typical system to reduce costs and improve efficiency, the liner shipping system has an important role in economic globalization. In recent years, with the government’s strengthening of carbon emission control and the popularity of liner alliances, the decision-making problems faced by liner companies have become more complicated. Motivated by this setting, this paper investigates a liner shipping network - transaction mechanism joint design problem (LSTD). The government’s levy of carbon taxes on liner companies and liner alliance cooperation strategies are considered. To solve the abovementioned problem, a biobjective optimization model is established. The model takes the total profit of the alliance and the fairness of the distribution of alliance profit as two objectives and optimizes the alliance liner shipping network design scheme (i.e., composition of the fleet, calling sequence of the ports on the routes, and sailing speed of ships) and the alliance transaction mechanism (i.e., slot transaction price among members). To solve the model, the biobjectives are set with different priorities to transform the model into a two-stage model. A genetic algorithm is designed and embedded into the inverse optimization model. Numerical experiments are performed based on China’s actual import/export transportation data. Two sensitivity analyses for different freight rates and carbon tax rates are conducted. The experimental results show that the proposed model and algorithm can effectively solve the LSTD and provide necessary decision support for the operation of the liner alliance.

Liner shipping network design with sensitive demand

Purpose This paper aims to examine containership routing and speed optimization for maritime liner services. It focuses on a realistic case in which the transport demand, and consequently the collected revenue from the visited ports depend on the sailing speed. Design/methodology/approach The authors present an integer non-linear programming model for the containership routing and fleet sizing problem, in which the sailing speed of every leg, the ports to be included in the service and their sequence are optimized based on the net line's profit. The authors present a heuristic approach that is based on speed discretization and a genetic algorithm to solve the problem for large size instances. They present an application on a line provided by COSCO in 2017 between Asia and Europe. Findings The numerical results show that the proposed heuristic approach provides good quality solutions after a reasonable computation time. In addition, the demand sensitivity has a great impact on the selected route and therefore the profit function. Moreover, the more the demand is sensitive to the sailing speed, the higher the sailing speed value. Research limitations/implications The vessel carrying capacity is not considered in an explicit way. Originality/value This paper focuses on an important aspect in liner shipping, i.e. demand sensitivity to sailing speed. It brings a novel approach that is important in a context in which sailing speed strategies and market volatility are to be considered together in network design. This perspective has not been addressed previously.

On the Liner Shipping Network Design. The Maritime Silk Route case study

On the Liner Shipping Network Design. The Maritime Silk Route case study

Container liner shipping network design with shipper’s dual preference

This paper addresses the container liner shipping network design by explicitly taking into account shipper's inertia preference and non-inertial preference. Firstly, using the double-constrained gravity model and Newton calibration method to predict the future OD demand matrix which is considered as the input of the model, and then the liner shipping company profit maximization is taken as the objective function to optimize the ship shipping routes, ship type and ship speed. A hybrid genetic algorithm is designed to solve CLSNDP (Container Liner Shipping Network Design Problem). We validate the proposed model by employing a real liner shipping network on the trade shipping route between Asia and West Europe. Through sensitivity analysis, it is found that the service level and market share of container liner shipping company can be improved by considering the dual preference of shippers. In the non-inertia preference of shippers, when cost preference of shippers is greater than time preference, using large ships (over 7000TEU) can achieve greater profits and realize the scale economies of lager ships.

A Branch-and-Price Algorithm for the Liner Shipping Network Design Problem

Maritime transportation is the backbone of the global economy and one of its most important segments is liner shipping. To design a liner shipping network is notoriously difficult but also very important since an efficient network can be the difference between prosperity and bankruptcy. In this paper, we propose a branch-and-price algorithm for the liner shipping network design problem, which is the problem of designing a set of cyclic services and to deploy a specific class of vessels to each service so that all demand can flow through the network at minimal cost. The proposed model can create services with a complex structure and correctly calculate the transshipment cost. The formulation of the master problem strengthens a known formulation with valid inequalities. Because of multiple dependencies between ports that are not necessarily adjacent and no defining state at any of the ports, the subproblem is formulated and solved as a mixed integer linear program. Strategies to improve the solution time of the subproblem are proposed. The computational study shows that the algorithm provides significantly tighter lower bounds in the root node than existing methods on a set of small instances.

Integrated Liner Shipping Network Design and Scheduling

In global liner shipping networks, a large share of transported cargo is transshipped at least once between container vessels, and the total transportation time of these containers depends on how well the corresponding services are synchronized. We propose a problem formulation that integrates service scheduling into the liner shipping network design problem. Furthermore, the model incorporates many industry-relevant modeling aspects: it allows for leg-based sailing speed optimization, it is not limited to simple or butterfly-type services, and it accounts for service-level requirements such as cargo transit time limits. The classic liner shipping network design problem is already a hard problem, and to solve the extended version, we propose a column-generation matheuristic that uses advanced linear programming techniques. The proposed method solves LINER-LIB instances of up to 114 ports and, if applied to the classic liner shipping network design problem, finds new best solutions to all instances, outperforming existing methods reported in the literature. Additionally, we analyze the relevance of scheduling for liner shipping network design. The results indicate that neglecting scheduling and approximating transshipments instead may result in the design of liner shipping networks that underestimate cargo transit times and their implications.

Reposition of empty containers of different life stages integrated with liner shipping network design

ABSTRACTThis paper integrates empty container reposition with container shipping network design considering the container life stages. A mixed-integer linear programming model is built to determine the liner shipping network, the initial launch ports of new containers, the ports for scrapping obsolete containers, the empty container reposition scheme and the containers of different life stages being used for a specific voyage. A case study is done by taking liner shipping among China, Japan and South Korea, Southeast Asia, Europe and the US as an example. The results show that over 93% of new containers are put into use in China while 63% of old containers are scrapped in Europe or the US, and 73% of containers used for packing cargoes from China to the US are those at the Decline Stage or the Exit Stage.

A new formulation for the liner shipping network design problem

AbstractThe liner shipping network design problem (LSNDP) is an important problem within liner shipping because a good network can reduce costs and increase profits. Given sets of ports, vessel classes, and demands between the ports, the problem is to design a network of cyclic routes and assign a vessel class to each route so that all demands can flow through the network at minimal cost. In this paper, we analyze a new formulation of the LSNDP based on a two‐layer network structure. The formulation takes into account the cost of transshipment and allows for complex service structures. Valid inequalities and a novel approach of inner representations of low‐dimensional polyhedra are proposed. A new set of small instances with up to 12 ports has been developed and the formulation has been tested on these instances. Instances with up to 10 ports are solved to optimality, but the largest instances are not, confirming that the LSNDP is a very complex problem. The proposed improvements of the formulation are also shown to have a positive effect.

Optimization in liner shipping

Seaborne trade is the lynchpin in almost every international supply chain, and about 90% of non-bulk cargo worldwide is transported by container. In this survey we give an overview of data-driven optimization problems in liner shipping. Research in liner shipping is motivated by a need for handling still more complex decision problems, based on big data sets and going across several organizational entities. Moreover, liner shipping optimization problems are pushing the limits of optimization methods, creating a new breeding ground for advanced modelling and solution methods. Starting from liner shipping network design, we consider the problem of container routing and speed optimization. Next, we consider empty container repositioning and stowage planning as well as disruption management. In addition, the problem of bunker purchasing is considered in depth. In each section we give a clear problem description, bring an overview of the existing literature, and go in depth with a specific model that somehow is essential for the problem. We conclude the survey by giving an introduction to the public benchmark instances LINER-LIB. Finally, we discuss future challenges and give directions for further research.

Liner shipping network design with emission control areas: A genetic algorithm-based approach

To curb emissions, containerized shipping lines face the traditional trade-off between cost and emissions (CO2 and SOx) reduction. This paper considers this element in the context of liner service design and proposes a mixed integer linear programming (MILP) model based on a multi-commodity pickup and delivery arc-flow formulation. The objective is to maximize the profit by selecting the ports to be visited, the sequence of port visit, the cargo flows between ports, as well as the number/operating speeds of vessels on each arc of the selected route. The problem also considers that Emission Control Areas (ECAs) exist in the liner network and accounts for the vessel carrying capacity. In addition to using the MILP solver of CPLEX, we develop in the paper a specific genetic algorithm (GA) based heuristic and show that it gives the possibility to reach an optimal solution when solving large size instances.

A flow‐first route‐next heuristic for liner shipping network design

Having a well‐designed liner shipping network is paramount to ensure competitive freight rates, adequate capacity on trade‐lanes, and reasonable transportation times. The most successful algorithms for liner shipping network design make use of a two‐phase approach, where they first design the routes of the vessels, and then flow the containers through the network in order to calculate how many of the customers’ demands can be satisfied, and what the imposed operational costs are. In this article, we reverse the approach by first flowing the containers through a relaxed network, and then design routes to match this flow. This gives a better initial solution than starting from scratch, and the relaxed network reflects the ideas behind a physical internet of having a distributed multi‐segment intermodal transport. Next, the initial solution is improved by use of a variable neighborhood search method, where six different operators are used to modify the network. Since each iteration of the local search method involves solving a very complex multi‐commodity flow problem to route the containers through the network, the flow problem is solved heuristically by use of a fast Lagrange heuristic. Although the Lagrange heuristic for flowing containers is 2–5% from the optimal solution, the solution quality is sufficiently good to guide the variable neighborhood search method in designing the network. Computational results are reported, showing that the developed heuristic is able to find improved solutions for large‐scale instances from LINER‐LIB, and it is the first heuristic to report results for the biggest WorldLarge instance.

Competitive Liner Shipping Network Design

We present a solution method for the liner shipping network design problem which is a core strategic planning problem faced by container carriers. We propose the first practical algorithm which explicitly handles transshipment time limits for all demands. Individual sailing speeds at each service leg are used to balance sailing speed against operational costs, hence ensuring that the found network is competitive on both transit time and cost. We present a matheuristic for the problem where a MIP is used to select which ports should be inserted or removed on a route. Computational results are presented showing very promising results for realistic global liner shipping networks. Due to a number of algorithmic enhancements, the obtained solutions can be found within the same time frame as used by previous algorithms not handling time constraints. Furthermore, we present a sensitivity analysis on fluctuations in bunker price which confirms the applicability of the algorithm.

Cooperative liner shipping network design by means of a combinatorial auction

Cooperation in the ocean liner shipping industry has always been important to improve liner shipping networks (LSN’s). As tight cooperations like alliances are challenged by antitrust laws, looser forms of cooperation among liner carriers might become a reasonable way to increase efficiency of LSN’s. Our goal is to facilitate a loose form of cooperation among liner carriers. Therefore, we introduce a coordination mechanism for designing a collaborative LSN based on a multi round combinatorial auction. Via the auction, carriers exchange demand triplets, i.e. orders which describe the transport of containers between ports. A standard network design problem which includes ship scheduling and cargo routing decisions is used as isolated network design problem of an individual carrier. A carrier has to solve this isolated problem repeatedly during the auction so that the carrier is able to decide which demand triplets to sell, on which demand triplets to bid, and what prices to charge. To solve these problems we propose a variable neighborhood search based matheuristic. The matheuristic addresses the isolated planning problem in four phases (construct ship cycles, modify cycles, determine container flow, and reallocate ships to cycles). Our computational experiments on a set of 56 synthetic test instances suggest that the introduced combinatorial auction increases profits on average compared to isolated planning significantly by 4%. The more diverse the original assignment of demand triplets and ships to carriers is, the higher the potential for collaboration; for 18 diverse instances, the profits increase on average by 10%.