Research on feeder network design: a case study of feeder service for the port of Kotka

An obvious change in the container shipping industry is the upsizing of container vessels. According to industry consultant Alphaliner, container vessels over 10,000 TEU (Twenty-Foot Equivalent Unit) account for 35% of the global fleet. With increasing usage of mega container vessels, cargo consideration at transshipment ports is now more important [1]. This transshipment may result from the limitation of port facilities or the economic evaluation of the market the port serves. The feeder line refers to the service routes that provide connection with trunk lines and plays an important part in transshipment. The feeder line service should not only realize efficient connection, but also expand service routes and feed the capacity. The competitiveness and stability of feeder networks are vital to the entire service network. However, there are few previous studies on feeder network design. The uniqueness of the feeder network design is not reflected in the evaluation system as current research takes trunk lines as a research object. In addition, the current research seems to be single objective as it evaluates cost or revenue, which is inconsistent with the characteristics of the participative observation. A multi-objective evaluation system is necessary to improve the current research, and this study intends to cultivate new ground in the current literature. We proposed a new optimization model from an actual case study of feeder network design for the port of Kokta, which proved to be effective through numerical experiment based on real life data.

Our main contribution is threefold. First, we propose a threex-stage control system for feeder network design, of which the main concepts are different from those of trunk lines. This solves the limitation for lack of evaluation of existing public services before the optimization model was proposed. The three-stage control system more realistically simulates the real decision-making process as the numerical experiment was derived from an author-involved case. Secondly, we propose a multi-objective decision-making system for feeder network design. This fills the current research gap that the optimization models were established via the single-objective evaluation of cost minimization or revenue maximization. Thirdly, we first propose including short-leg cargos (in this case, intra-European cargos) in the feeder network evaluation. This means we evaluate both long-haul and short-leg cargos in the shipping network design, which fills the current research gap regarding short-leg cargos.

The remainder of the paper is organized as follows. Section 2 presents a literature review and analyzes the research gap. Section 3 discusses the feeder network design problem. Section 4 formulates a feeder network design model and proposes alternatives based on historical data from a case study. Section 5 analyzes the results and investigates the underlying reason. Section 6 presents concluding remarks.

In recent decades, the service network design problem has drawn significant attention in maritime studies. We first introduce some studies on general network design problem in container shipping. An example of a study analyzing a hub-and-spoke network design is an article by Gelarth, Maculan, and Mahey [2] which studied these two aspects in regards to container shipping. They proposed a mixed integer linear programming model and a Lagrangian decomposition approach was adopted as a solution. Information regarding the general problem of fleet deployment focusing on trunk and feeder lines can be found in the following studies: Everett et al. [3] (the first to study the fleet deployment problem), and Perakis and Jaramillo [4] who further expanded the research in this field. Interested readers can refer to the study by Meng et al. [5] for an overview of these studies.

Network design problem always examined considering cargo routing and some other practical factors. Hwa-Joong, Lee, and Tae-Woo [6] investigated the potential trunk lines and transshipment flows in the network design problem. In an effort to make the network design problem more practical, Shintani et al. [7] examined the network design problem with empty container repositioning. Santini, Plum, and Ropke [8] investigated a feeder network design by considering the operational characteristics. The container transport demand is uncertain during network design and cargo assignment periods [9]. Some studies used this uncertain demand as an input to model a stochastic cargo assignment problem. Meng, Wang, and Wang [10] developed a two-stage integer programming model to examine the fleet deployment and routing management problems over a short-term planning horizon. There are also studies addressing inland waters and special waterways. Zheng and Yang [11] studied the network design for container shipping along the Yangtze River. The study proved economies of scale do exist on certain segments of the Yangtze River’s service network. Zhao, Hu, and Lin [12] studied the network design problem in the context of the Northern Sea Route. They used a two-stage model where the first stage involved selecting a set of ports and the second stage involved designing the network.

We identified the following gaps in the current research on container liner shipping practices:

First, a single decision-making objective does not reflect the multi-objective behaviors of liner shipping in practice. The current research was based largely on the maximization of revenue, profit, or minimization of cost (e.g.,Hwa-Joong et al. [6] and Santini et al. [8]). However, in practice, the decision objective was made in reference to a host of factors including: cost, sailing cycle, equipment balance, allocation utilization, service route competitiveness, and stability. The equipment balance and allocation utilization assess the corresponding capability of the empty container provision and resource utilization efficiency. A single-objective decision-making process is not comprehensive enough and does not consider all the necessary variables.

Second, the implicit hypothesis of these studies was to allocate the vessels within specific calling ports. However, there is no comparison between the designed service network and the exchanging service routes from shipping alliance members or the common feeders. This may lead to one-sided conclusion.

Thirdly, most of the existing research focused on trunk lines but rarely on feeder lines. The different characteristics of feeder lines spur different research ideas. Santini et al. [8] proved that it was unnecessary to consider transshipment in feeder network design. However, the other characteristics of feeder network design were not studied.

In particular, to the best of our knowledge, no research has examined feeder network design from the viewpoint of intra-Europe or intra-Asia business position rather than just the connection for the trunk line. This is precisely where the contribution of the study lies.

The large scale of container vessels has significantly changed the service network design, resulting in the hub-and-spoke system in widely application. Konings et al. [13] concluded that feeder vessel operators benefit from the shorter turnaround times and productivity improvement in the hub-and-spoke system. The port of Kotka (Finland) is a typical out port in the hub-and-spoke network. As ocean carriers do not provide direct service to Kotka on the main east-west trade lanes, the port is heavily reliant on the feeder service from the hub ports of Rotterdam (the Netherlands) and Hamburg (Germany). Feeder liner companies such as Unifeeder and Xpress provide regular services to connect the port of Kotka with various ports in the Netherlands, Germany, Russia, Poland, and Denmark. Figure 1 presents a main service route in the Baltic Sea ports.

The common feeder services extend the hinterland market to out ports and lay a foundation for improving vessel utilization. However, an ocean carrier’s individual demand cannot be satisfied as a result of the common feeder services’sailing frequency, calling ports and delivery time are designed by the common operators. In addition, ocean carriers have limitations in exploiting intra regional cargos due to the fact that short-leg slots are restricted. Carriers are also under continual cost pressure due to the fact that feeder vessel operators are relatively concentrated in certain geographical areas.

The ocean carrier Company A used to connect the port of Kotka through common feeder services by transshipment from the port of Hamburg and Rotterdam. This limitation became more pronounced with the upgrading of fleet capacity deployed in Europe and the Mediterranean region.

Company A kept statistics on its cargo volume and found that the port of Kotka’s average import and export cargo volume only reached between 324 TEU and 370 TEU per week. This quantity is not adequate to support its own feeder service; however, it seems to be a practicable solution if the feeder service also connects with various ports in Denmark, Poland and Russia. In addition, having its own feeder service can also provide the company a path for empty container repositioning among different ports, and make it possible to develop the Intra-European business. The decision to move forward with its own feeder service hinges on whether it is more cost-efficient and competitive when compared to the common feeder service, but there are other factors to consider, as well. Given this complexity, it is important to develop a robust decision-making process that takes into account multiple key variables including: cost, equipment balance, allocation utilization and Intra-European cargo revenue, among others. We present a three-stage control method addressing this issue.

Our recommendation is a three-stage optimization model analyzing the decision-making process based on the relevant observations. The first stage calculates the historical cargo volume transported by Company A on possible calling ports. We make an evaluation of the cost competitiveness of the company’s own feeder service, comparing it to the common feeder service by assigning appropriate vessel types according to the historical cargo volume. The second stage presents an optimization model and proposes the alternative of a feeder service for the port of Kotka. We present the difference in the decision-making process by evaluating the revenue of intra-European cargos compared to traditional methods. The third stage proposes a multi-objective evaluation system for the alternative schemes through Grey correlation combining the indicators of cost, sailing cycle, equipment balance, service route competitiveness, stability, and Intra-European cargo revenue.

A different priority for the feeder network scheme is presented in section 4. By evaluating the total sailing cost, the order of preference is found to be Scheme 4, 1, 2 and 3. This type of system is representative of the current research. The disadvantage lies in the lack of information on cost difference by the numbers of vessels deployed and calling ports, and it also fails to evaluate the impact of the extra cost on the revenue. The SAC evaluation system seems to improve the weakness of the above system as the total sailing cost is apportioned in the service route network. In this case study of section 4, the order of preference is Scheme 1, 2, 4 and 3 according to the order of SAC. Although this method is widely applied to practice, the impact of revenue generated by the additional service route is still not evaluated. By evaluating the revenue generated;the analysis reveals that certain cost increase is necessary and beneficial to the network design. This can be verified by the numerical experiment in section 4, Schemes 1 and 3 seem to be superior to other schemes as the result of more effective service routes. This advantage depends on the cargo transported, which is also reflected as the AU of effective port pairs. From the numerical experiment, the advantages of Schemes 1 and 3 can be realized only after a certain quantity of cargo is achieved. On this basis, we further investigate the service and efficiency indicators such as the EB, SRC, and stability. The priority of Schemes 3 and 1 is found to be reversed. This can be attributed to the fact that the double hub ports design provides more possibilities for EB, optimizes the connection between feeder liners and trunk lines, and improves the competitiveness of the feeder network.

Feeder network design is best analyzed by a typical multi-objective decision–making model. In addition to the layout optimization of service routes, a feeder network provides efficient connection with trunk lines, establishing more effective port pairs to generate more revenue, improve equipment balance, and maintain the stability and competitiveness of the route. Therefore, the single objective evaluation model in the current researches has limitations. This study presents a multi-objective optimization model to reflect the main variables indicators for feeder network design. According to the Grey correlation method analysis, the allocation utilization seems to have a great impact in the decision–making process. This directs us to pay more attention to the efficiency of resource utilization in practice. Equipment balance and service stability both have significant impact as a result of the high correlation of these indicators with cost and customer service in feeder network design. The intra-regional cargo revenue is another key indicator that determines both feeder and trunk line design and has a major impact on the decision- making process as well. This indicates that it is important to evaluate the benefits of both long-haul and short-haul allocations in a practical service network layout. In a word, the objectives of service network design are diversified from the perspective of practical management. The multi-objective control model proposed in this paper reflects key factors in the actual decision-making process, which has significance for industry professionals.

This paper also has limitations as no sensitivity analysis was conducted to examine the sensitivity of each indicator. Further research is necessary to examine how a feeder network design is affected by extended cooperation and competition between both the members in shipping alliances and also the common feeder operators.