Container Routing Research Articles

Ship Type Selection and Cost Optimization of Marine Container Ships Based on Genetic Algorithm

In the context of the deep-sea transportation supply chain, this paper addresses the complex decision-making problem of vessel allocation and carbon emission optimization for container shipping routes. A bi-level programming model is established, with the upper level aiming to minimize the total operational cost and the lower level focusing on minimizing carbon emissions. Using an example of an operator with five different types of vessels, a genetic algorithm is employed to determine the optimal vessel allocation scheme. The results indicate that the vessel allocation scheme obtained through multiple iterations of the model effectively reduces both carbon emissions and operational costs. Under the condition that the preset labor cost increases year by year, the use of model optimization can significantly reduce the growth of total operating costs. This paper provides theoretical support and practical guidance for shipping companies aiming to optimize decision-making in order to reduce operational costs and carbon emissions.

Ship routing in inland waterway liner transportation with foldable and standard empty containers repositioning

This paper addresses the container ship routing problem in inland waterway liner transportation. Given estimated weekly full container shipping demands between port pairs and the potential empty container demands at each port, our goal is to design the container ship route and determine the amount of foldable and standard empty containers to be shipped between each port pair in the context of navigational restrictions, so as to maximize the profit of the shipping services. To save possible leasing or storage costs of empty containers at various ports and meet navigational restrictions, the release of foldable containers and the repositioning of empty containers were taken into account in the decision. Two mixed integer programming models are established to optimize ship route and shipping strategies under splittable and unsplittable demands. The models are further improved by projecting arc variables for simulating the transportation of empty containers, and the improved model has fewer decision variables and higher computational efficiency. Numerical experiments based on the Yangtze River are conducted to test the applicability of methods. Finally, some reference recommendations are presented.

Monopoly in the container shipping market: an econometric approach

PurposeSince the 2010s, market conditions for container shipping companies have been deteriorating owing to decreasing container cargo trade and increasing supply capacity. This study aims to contribute to the empirical literature on the container shipping industry market structure. Specifically, this study aims to investigate the extent of market competition.Design/methodology/approachThis study analyzes the market structure and evaluates the market power of shipping companies through a non-structural test.FindingsThe H-statistic for the entire period of 2004–2018 was 0.37, which is significantly different from zero. This indicates the absence of monopoly pricing throughout the entire period. For the time-phased estimates, the H-statistic between 2004 and 2008 is 0.15, which is not significantly different from zero. On the other hand, the H-statistic from 2009 to 2018 was 0.40, which differs significantly from zero.Originality/valueAs the Far East Freight Conference had released tariffs and charge rates by item for container shipping routes, monopolistic pricing is said to have appeared until the European Union abolished the European Economic Community (No. 4056/86) in 2008, before the economic crisis. However, this study indicates that pricing in the container shipping industry has been distinctly non-monopolistic; further, competition seems to have intensified since 2008. Industry competitiveness is of interest not only to academics but also to practitioners, including policymakers, especially when considering competition policies.

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.

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.

Liner Shipping Schedule Design for Near-Sea Routes Considering Big Customers’ Preferences on Ship Arrival Time

There usually exist a few big customers at ports of near-sea container shipping routes who have preferences on the weekly ship arrival times due to their own production and sale schedules. Therefore, in practice, when designing ship schedules, carriers must consider such customers’ time preferences, regarded as weekly soft-time windows, to improve customer retention, thereby achieving sustainable development during a depression in the shipping industry. In this regard, this study explores how to balance the tradeoff between the ship total operating costs and penalty costs from the violation of the weekly soft-time windows. A mixed-integer nonlinear nonconvex model is proposed and is further transformed into a mixed-integer linear optimization model that can be efficiently solved by extant solvers to provide a global optimal solution. The proposed model is applied to a near-sea service route from China to Southeast Asia. The results demonstrate that the time preferences of big customers affect the total cost, optimal sailing speeds, and optimal ship arrival times. Moreover, the voyage along a near-sea route is generally short, leaving carriers little room for adjusting the fleet size.

Assessment of relative fuel cost for dual fuel marine engines along major Asian container shipping routes

This study contributes to academic literature on bunkering for liner shipping with the application of dual fuel engines in providing fuel flexibility subjected to limited liquefied natural gas (LNG) bunkering facilities along a subset of the major shipping lanes East of Suez. New LNG bunkering facilities have developed in recent years which is critical to the uptake of LNG as a bunker fuel while with the installation of dual fuel engines, vessels operators will now have a choice regarding the main fuel for propulsion. An additional layer regarding the combinatorial aspect of different fuel types to utilize as well choice to bunker at LNG facilities enroute (not calling port) is incorporated subjected to maintaining weekly schedules by speed adjustments.

Spatial variation of travel time uncertainty in container shipping

Container shipping plays an important role in economic development by providing services for unitized cargos on fixed ocean trading routes between destinations. The transit time, as well as freight cost, presents temporal and monetary costs in the global trade system. Given the fixed routing characteristic in container shipping, a study on the reliability of travel times is crucial to understand the dynamics on temporal cost in major international trades. This research investigates empirically whether there exist spatial differences in international container shipping routes by employing actual shipment data for a fleet of over 600 container vessels extracted from the Automatic Identification System (AIS). The results show that the geographic distribution of the routes have significant impact on travel time uncertainty and hence there is clear variation across international trade routes. Sailing route security, infrastructure and trade volumes in the routes are likely the underlying explanations. This research contributes to the literature in two folds. We pioneer in modelling the micro-level container invisible trade cost by computing the service uncertainty. This also provides insight of the temporal cost of international container cargo trade in terms timing reliability and its dynamic structures.

Optimal port call adjustment for liner container shipping routes

Container shipping companies usually alter their shipping networks in response to the seasonally changing shipping demand and freight rate. Rather than redesigning their shipping networks from scratch, they often choose to make small adjustments to the shipping routes by skipping some ports or adding additional calls to several ports. Inspired by above industrial practice in shipping network alteration, this study solves the port call adjustment problem (PCAP) to determine which port calls should be removed and which should be inserted for each route of a shipping network under the new shipping market patterns. A two-phase solution method is developed for the PCAP. In Phase 1, the candidate port calls for removal and insertion operations in each shipping route are determined. In Phase 2, the port call adjustment strategy is obtained by solving a mixed integer linear programming (MILP) model to select the port calls from these candidates identified in Phase 1 for actual removal and insertion operations. Considering the difficulties in solving the MILP model efficiently, two heuristic methods are also proposed to give near-optimal solutions in an acceptable computational time. Numerical experiments demonstrate that the proposed two-phase method is able to find a port call adjustment strategy that significantly reduces the operating cost.

Some Main Causes of Marine Pollution in Vietnam

Vietnam is a coastal country located in the central region of Southeast Asia, Vietnam has a sea area connecting the important sea transport route between the Indian Ocean and the Pacific Ocean, especially the East Vietnam Sea are oil and container shipping routes from other countries to Japan, South Korea and China, which are consuming huge amounts of energy. Vietnam is in a position to have a potential for marine economic development such as shipbuilding, sea transport, port development, and waterworks, marine product exploitation, marine and oil and gas resource exploitation, marine tourism and islands, sea services, and other related industries. With such a potential position, the exploitation of the sea and the protection of the marine environment is an extremely important issue.

Some Main Causes of Marine Pollution in Vietnam

Vietnam is a coastal country located in the central region of Southeast Asia, Vietnam has a sea area connecting the important sea transport route between the Indian Ocean and the Pacific Ocean, especially the East Vietnam Sea are oil and container shipping routes from other countries to Japan, South Korea and China, which are consuming huge amounts of energy. Vietnam is in a position to have a potential for marine economic development such as shipbuilding, sea transport, port development, and waterworks, marine product exploitation, marine and oil and gas resource exploitation, marine tourism and islands, sea services, and other related industries. With such a potential position, the exploitation of the sea and the protection of the marine environment is an extremely important issue.

Terminal Vitalization Strategy through Optimal Route Selection Adopting CFPR Methodology

Container shipping route selection strategy has become an important component in attracting additional cargo volumes and increasing terminal competitiveness of small and medium ports (SMPs). Shipping route selection relies upon decisions based on real industry data and expert judgments. There is scant research that places emphasis on container shipping route selection as a vital aspect of SMPs. This paper bridges the gap by utilizing Consistent Fuzzy Preference Relations (CFPR) methodology, which handles both qualitative and quantitative factors in order to select optimal routes for SMPs. Donghae port, which is located on the east coast of South Korea, is analyzed as a case study. The results illustrate that volume commitment ranks first among the 19 established selection factors, followed by incentive system risk and head-haul ratio. This study also reveals that Donghae-Hochiminh is the optimal route for the Donghae port, while the container shipping route of Donghae-Port Kelang is ranked in the middle, and Donghae-Jakarta is considered to be the least optimal route amongst the three alternatives.

Designing Container Shipping Routes for Heterogeneous Fleet for Coastal Services

Shipping companies operating liner services keep facing a high level of competition because of the increasing demand for these operators to provide fast, efficient, effective and reliable service. It is challenging for these liner operators to offer such services and still be competitive without strategic planning. It, therefore, makes planning and scheduling of shipping routes essential for the smooth operation of liner ships, especially shipping lines operating heterogeneously mixed size fleets. This paper aims to solve a heterogeneously mixed size fleet problem by using an operation research method with the implementation of linear programming to develop optimal shipping routes for a fleet of five vessels serving six coastal ports to get optimal results. An optimal solution to the problem is found with only two routes selected as the optimal shipping routes out of four routes that are considered. The results also showed that a vessel can be assigned to multiple shipping routes.

Study on the Impact of the Panama Canal Expansion on the Distribution of Container Liner Routes

The expansion of the Panama Canal will have a profound impact on the container shipping route network, port layout and ship structure, and promote the evolution of the global shipping pattern. However, most of the research on the expansion of the Panama Canal currently stays before its real expansion, and the quantitative analysis is less and the result is not accurate, because previous research used data that expanded before. Based on the actual data after the expansion of the Panama Canal, this paper uses the dual-target route distribution model to analyze the expansion of the Panama Canal. The changes in the liner shipping plan that have a greater impact on the shipping industry will provide the relevant theoretical basis for the relevant entities. The results show that after the expansion of the Panama Canal, the largest 15,000 TEU container ship is currently deployed on the route through the Panama Canal. 6500 TEU ship type is also deployed on the route through the Panama Canal. The 8500 TEU, 10,500 TEU, and 12,500 TEU ship types are mainly deployed through the Suez Canal. On the route, such a distribution plan can maximize the benefits for the shipping company.

Analyzing Congestion Interdependencies of Ports and Container Ship Routes in the Maritime Network Infrastructure

Events, such as prolonged congestion in ports or unavailable ship routes in the maritime network, often initiate cascading congestions that block transportation and/or disrupt services over wide areas. Existing traffic flow analysis methods lack the ability to understand the cascading effects of delays in ship routes or how to reduce overall delays in greater maritime areas. Dependency risk graphs have been proposed as a tool for analyzing such cascading events using dependency chains. This paper proposes a risk-based interdependency analysis method capable to detect large-scale traffic congestions between interconnected ports and ship routes in the maritime network and provide solutions to improve flow. Presented dependency risk chains of ports along with graph theory help us analyze ship routes and detect ports that are affected most when other major ports are congested in the maritime network, detect the causes of bottlenecks, and provide valuable info in relieving delays across container ship routes. We apply the proposed method on historical container ship routing data provided by the MarineTraffic company that maintains a comprehensive maritime database worldwide for more than six million users monthly. This application-oriented, interdisciplinary effort culminated in a prototype tool is able to analyze the historical data for container ships in the entire global maritime network and detect congestion dependencies. The tool can be used to identify key shipping routes or ports that: 1) are prone to delays; 2) greatly affect the overall maritime network due to position, connections and risk of congestion; and/or 3) get affected the most by delays in previous route legs.

Economic evaluation on container shipping route selection

The competition between each attractive container cargo port has been increasing drastically. Every port is striving to maintain the competitive edge and provide satisfactory services. This paper will provide an economic evaluation model which corresponds to the change of transshipment cargo volume of neighbour ports in North East Asia. The model, which classifies to Route 1 and Route 2, figures out an economic evaluation of the sea route, both routes hypothesise the Busan Port as a starting point. Basing on this model, it can generate an important data for deciding sea routes and calling ports of the shipping companies. Moreover, the shipping companies could improve a more efficient route and the related government authority or operational institution of each country could figure out the threshold of feeder cargo volume through this economic method.

Economic evaluation on container shipping route selection

Economic evaluation on container shipping route selection

Tighter MIP models for Barge Container Ship Routing

This paper addresses the problem of optimal planning of a liner service for a barge container shipping company. Given estimated weekly demands between pairs of ports, our goal is to determine the subset of ports to be called and the amount of containers to be shipped between each pair of ports, so as to maximize the profit of the shipping company. In order to save possible leasing or storage costs of empty containers at the respective ports, our approach takes into account the repositioning of empty containers. The line has to follow the outbound–inbound principle, starting from the port at the river mouth. We propose a novel integrated approach in which the shipping company can simultaneously optimize the route (along with repositioning of empty containers), the choice of the final port, length of the turnaround time and the size of its fleet. To solve this problem, a new mixed integer programming model is proposed. On the publicly available set of benchmark instances for barge container routing, we demonstrate that this model provides very tight dual bounds and significantly outperforms the existing approaches from the literature for splittable demands.We also show how to further improve this model by projecting out arc variables for modeling the shipping of empty containers. Our numerical study indicates that the latter model improves the computing times for the challenging case of unsplittable demands. We also study the impact of the turnaround time optimization on the total profit of the company.

Container shipping route design incorporating the costs of shipping, inland/feeder transport, inventory and CO2 emission

As container shipping networks have become important components in global supply chains, route design should take both maritime and inland factors into consideration. In this article, a model is proposed to optimise container flows between two continents via an end-to-end service. The model is concerned not only with the design of an optimal shipping route but also with inland connections between hinterlands and ports. The objective is to minimise total costs, consisting of ship costs, port costs, inland/feeder transport costs, inventory costs and CO2 costs. The model is applied to the actual trade between Europe and the United States. Computational outcomes show that ship costs and port costs (port dues and terminal handling charges) represent less than one third of total costs. Therefore, the maritime network is only a part of a bigger system and piecemeal optimisation may not guarantee the optimisation of the whole network. Inland/feeder transport costs contribute the most to total costs, and they are influenced significantly by port choice. Although the use of a greater number of ports results in longer distances and higher shipping costs, this benefits in terms of lower distribution costs between hinterlands and ports. Inventory costs play a considerable part in total costs and they increase as vessel capacity goes up. In other words, these costs present a barrier to the introduction of bigger vessels. Optimal size is obviously a trade-offs between inventory and shipping costs.

Analysis of Profitability for Container Shipping on Arctic Routes by Navigation Speed and Risk of Disruption

Arctic sea routes have long been a worldwide focus because they create shorter distances between the Atlantic and the Pacific Oceans and because of their role in relieving pressure on the two busiest traditional routes for maritime shipping. Models used to address the profitability of Arctic shipping have neglected the variety of navigation speeds along Arctic routes related to various ice situations in the Arctic zone. As well, risks of disruption and recovery costs are seldom taken into account in the models. To improve the accuracy of assessments, this paper analyzes disruptions and delays along Arctic container shipping routes and presents a nonlinear programming model for minimizing operation costs, including penalties for deviations in arrival time and for undelivered containers. Piecewise linear interpolation is used to transform this nonlinear problem into a mixed-integer linear programming problem. Results of a case study are discussed for validity and improvements. This study could help shipping liners design a service network of container shipping through the Arctic routes.