Inland Container Transportation Research Articles

Modeling and Optimization of the Inland Container Transportation Problem Considering Multi-Size Containers, Fuel Consumption, and Carbon Emissions

This paper investigates the inland container transportation problem with a focus on multi-size containers, fuel consumption, and carbon emissions. To reflect a more realistic situation, the depot’s initial inventory of empty containers is also taken into consideration. To linearly model the constraints imposed by the multiple container sizes and the limited number of empty containers, a novel graphical representation is presented for the problem. Based on the graphical representation, a mixed-integer programming model is presented to minimize the total transportation cost, which includes fixed, fuel, and carbon emission costs. To efficiently solve the model, a tailored branch-and-price algorithm is designed, which is enhanced by improvement schemes including a heuristic label-setting algorithm, decremental state-space relaxation, and the introduction of a high-quality upper bound. Results from a series of computational experiments on randomly generated instances demonstrate that (1) the proposed branch-and-price algorithm demonstrates a superior performance compared to the tabu search algorithm and the genetic algorithm; (2) each additional empty container in the depot reduces the total transportation cost by less than 1%, with a diminishing marginal effect; (3) the rational configuration of different types of trucks improves scheduling flexibility and reduces fuel and carbon emission costs as well as the overall transportation cost; and (4) extending customer time windows also contributes to lower the total transportation cost. These findings not only deepen the theoretical understanding of inland container transportation optimization but also provide valuable insights for logistics companies and policymakers to improve efficiency and implement more sustainable operational practices. Additionally, our research paves the way for future investigations into the integration of dynamic factors and emerging technologies in this field.

Container drayage problem integrated with truck appointment system and separation mode

Growing demand for seaborne trade has exacerbated the challenges faced by drayage operators in inland container transportation. In some cases, drayage operators must make truck scheduling decisions and book periods for trucks to visit terminals daily. This paper considers the appointment system and separation mode in container drayage problem, which consists of delivery and pickup transportation tasks for empty and full containers. A mixed-integer linear programming model is developed to minimize the total truck operating time while solving the truck scheduling problem, the empty container allocation problem, and the appointment problem. Another key feature of the model is considering the temporal constraints between tasks from a more realistic perspective. Due to the complexity of the problem, it is not practical to obtain exact solutions for large instances. Therefore, we complete the implementation of a new genetic algorithm (GA) that introduces a topological sort tailored to this problem. Several experiments and analyses are used to demonstrate the correctness of the proposed model as well as the efficiency of the algorithm. The findings indicate that, when compared to traditional mode, separation mode can reduce total truck operating time by an average of 29.4%. The total truck operating time difference between the two modes shows an overall positive trend if the task size increases. In addition, a rational setting of the appointment system will have a beneficial effect on truck scheduling. The decision on the selection of periods and the increment of each quota is crucial in optimizing the setting of the appointment system to reduce the total truck operating time for the mutual benefit of both terminals and drayage operators.

Analyses of port infrastructure investment and shore power subsidy policies for inland container transportation network with CO<SUB align="right">2 emission reduction targets

Analyses of port infrastructure investment and shore power subsidy policies for inland container transportation network with CO<SUB align="right">2 emission reduction targets

Container Scheduling considering Customer Satisfaction in the Context of Internal Circulation

As China’s foreign trade continues to progress, a trade surplus in inland container transportation has emerged. At the same time, businesses need to not only focus on transportation tasks but also prioritize customer service requirements. To address the issues of container supply shortages and inefficient empty container allocation, this article establishes a container truck scheduling model that includes multiple terminals and yards. With the objective of minimizing total costs and maximizing customer satisfaction during the allocation process, the model incorporates coupling constraints between vehicle flow and container flow. Instance verification using Cplex demonstrates that the proportions of different cost types and the range of expected time windows can impact the formulation of transportation plans and, consequently, total costs. Lastly, numerical experiments are conducted to analyze the cost variations and transportation plan preferences under different ranges of time windows and different weights assigned to transportation costs and fixed costs.

Integrated Location Selection and Scheduling Problems for Inland Container Transportation

Well-organized network configuration is the key to the success of inland container transportation systems. In this study, we firstly propose an integrated framework for the location selection of inland container depots (ICDs) and the scheduling of containers and trucks. The objective is to minimize the total cost of setting up the ICDs and transportation cost associated with trucks and containers. A mixed-integer linear programming (MILP) model is developed to solve the proposed problem. The computational studies show that the proposed decision approach is effective and can reduce the total operating costs of ICDs and transportation costs of containers. Sensitivity analysis on the impact of customer distributions and the number of ICDs on the total cost are conducted to reveal the characteristics of the problem. The utilization of ICDs can significantly improve the efficiency of the transportation network, i.e., the total cost is reduced by at least 27% for the proposed instances, and the transportation distance of empty containers is reduced by at least 4%. Finally, managerial insights and future research directions are provided.

안전운임제 하의 컨테이너 내륙 운송사 선정요인에 관한 연구

As the container freight rate is fixed with the implementation of the safe freight rates system for trucks in 2020, the freight factor can no longer function as a differentiated factor for shippers. As a result, domestic container inland transportation companies have become the main competitive factors for corporate’s characteristics and service-related factors, excluding cost factors in order to attract shippers. This study aims to suggest implications for the competitive strategy of shipping companies by deriving the priority of factors in selecting inland container transport truck companies for domestic shippers under circumstances excluding freight factors. Based on previous studies, four factors, i.e. company characteristics, service quality, service diversity, and additional service were pairwise-compared to determine relative priorities of alternative choices including four sub-criteria of each using AHP(Hierarchy Analysis Process). As a result, the overall ranking of main criteria of selection carrier is service quality factors, service diversity factors, additional service factors, and company characteristics factors in the order, and the priority of quality factors was revealed to be quite high compared to other factors. In detailed sub-factors, accident response capabilities, responsiveness of order, delivery on time, flexible dispatch time of vehicle, and information exchange and sharing were drawn in the order, confirming that quality, the essence of transport service, is of importance. Inland container carriers should strengthen their efforts to improve quality factors such as accident response capabilities, responsiveness of order, and delivery on time to enhance their competitiveness.

Optimizing inland container logistics through dry ports: A two-stage stochastic mixed-integer programming approach considering volume discounts and consolidation in rail transport

It is essential for container shipping companies to plan for the optimum number and locations of dry ports as well as efficient inland container logistics operations to reduce costs and environmental impacts while improving customer service. The plan for optimum inland container transportation network design must account for demand uncertainty to eliminate financial difficulty due to redundant investment. In this regard, this study proposed a two-stage stochastic mixed-integer programming model for optimizing inland container logistics through dry ports. The model contributes to the state of the art in current research by including a piecewise-linear cost function for railway transportation to account for volume discounts, integrating full container scheduling with transport mode selection and empty container relocation for consolidation, and reflecting the fact that the amount of import and export full containers transported between customers (consignees and consignors) and seaports are exogenously decided. The solution results demonstrated the definite performance superiority of the progressive hedging algorithm over the extensive form solution. Additionally, the value of stochastic solution calculation showed that the application of stochastic solution might result in significant cost savings compared to the application of mean value deterministic solution. The proposed model can be applied for practical necessities to design robust optimum inland container logistics operations using intermodal rail transport with the progressive hedging algorithm as an efficient solution approach.

A Physical Internet (PI) based inland container transportation problem with selective non-containerized shipping requests

The imbalance of inbound and outbound containers generates large numbers of idle runs of container trucks in inland container transportation. In tradition, the trucking company acquires shipping requests from the spot market to increase profitability, with the precondition that both origin and destination locations of the acquired request are the same as the idle travel. Such precondition undoubtably leads to limited benefits and poor stability, given that shipping requests from the spot market are of high randomness. This paper proposes to adopt the idea of Physical Internet (PI) and assign an acquired request to several trucks, allowing transfers from one truck to another at logistics hubs. In this way, temporally and spatially dispersed idle resources could be consolidated to achieve the shipments of selective shipping requests, in a relay manner. To our knowledge, this paper is among the first to study the new paradigm of inland container transportation and formally model it as a PI-based selective vehicle routing problem (PI-SVRP). A mixed integer program (MIP) is presented and validated with CPLEX on small instances. In order to tackle real world instances, several novel heuristics have been designed particularly according to the special problem structure and embedded into an adaptive large neighborhood search (ALNS) framework. Finally, substantial instances are generated based on real data and a series of numerical studies are performed to derive managerial implications for practitioners.

The future container throughput for inland shipping on the traditional Rhine: a SARIMAX approach

Inland container shipping is confronted with significant challenges, both on the demand and supply side. In line with the 2019 Green Deal’s ambitious goals and 2020 Sustainable and Smart Mobility Strategy, the European Commission presented an ‘Inland Waterway Transport Action plan 2021-2027’ with the target of shifting more freight across inland waterways. However, the COVID-19 pandemic together with the low water level raise interest in how these could impact the throughput for container transport on the inland waterways. In this research, the scope is on the container throughput for inland container transport on the traditional Rhine. This study first identifies the market drivers for containerized inland navigation in the medium run and then selects the SARIMAX method to analyse Inland Waterway Transport (IWT) volumes. The model application shows that the throughput for inland container transport on the traditional Rhine is impacted on by periods of low water and the weakening of the economy caused by COVID-19. The results of the study suggest that if the IWT container market is impacted by the identified factors, the throughput for containerized IWT is expected to decline by 8.9% in 2023 relative to the volumes in 2020. The research might act as a decision support tool for analysis, management and planning for policymakers and stakeholders.

The Inland Container Transportation Problem with Separation Mode Considering Carbon Dioxide Emissions

This paper investigates the Inland Container Transportation (ICT) problem with carbon dioxide emissions. The separation mode that the tractor and semi-trailer could be detached and it permits multitasking to reduce fuel and carbon emission costs. A mixed-integer programming model with Full-Empty container integration has been built. An improved ant colony optimization with two-dimensional variable matrix encoding and Infeasible-Arc filtration strategy has been proposed. Numerical experiments with different scales and characteristics are simulated and validated in order to demonstrate the effectiveness of the proposed algorithm. The comparison result indicates the excellent stability for our approach with different task characteristic distribution.

Modal Choice Preferences in Inland Container Transport in Poland

Purpose: As part of this paper, three research goals were set. The first one concerns the identification of factors influencing the modal choice to carry intermodal transport units by inland transport. The second goal is related to determining what conditions would have to exist for a given operator to agree to shift the cargo from road to rail transport as part of the modal shift concept. The third goal is to specify the influence of COVID-19 on the modal choice. Design/Methodology/Approach: Earlier studies have confirmed the difficulty in determining modal choice preferences due to their complexity. The complexity of the problem makes the use of quantitative methods ineffective. On the basis of the qualitative research conducted with the use of the in-depth semi structured interview, the authors identified the factors influencing the modal choice, at the same time defining the conditions that would have to be met in order to encourage cargo operators to make greater use of rail transport. Findings: The conducted research study indicated differences in the factors determining the choice of transport modes, mainly depending on the size of the surveyed company. The above-mentioned factors in relation to the entire study group included the time and cost of transport, as well as the availability and quality of transport infrastructure. The surveyed enterprises agreed that the factors that would have to occur to increase the use of rail transport included: increasing the number of reloading points at railway connections and increasing the timeliness of transport. Practical Implications: The results of the research can be used by decision-makers in formulating the directions of development of the transport system, and the entities responsible for the implementation of specific transport infrastructure investments, covering both linear and nodal elements. Originality/Value: The added value of this article is predicated on original research related to the determination of the premises for the selection of the transport mode in freight container transport in Poland. Requirements that could be a stimulus for implementing the modal shift idea in Polish companies. The authors confronted the research results achieved with the current scientific knowledge in this area, in addition, they also raised the topic of the Covid-19 pandemic and its impact on modal choice.

Impact analysis of different container arrival patterns on ship scheduling in liner shipping

ABSTRACT Different transportation modes interrelate in intermodal transportation. Previous researches on intermodal transportation mainly investigate policy, network design, cargo routing or drayage operations. In order to explore the coordination between two connected transportation modes, this paper considers the connection between inland transportation and maritime container transportation. By making use of different container arrival patterns resulted from inland transportation, this paper focuses on liner ship scheduling with sailing speed optimization, as well as considering the container storage cost at each port. The studied problem is formulated as a mixed-integer nonlinear programming model, which is efficiently solved by using an outer-approximation method. Numerical results show that the optimal ship schedule varies with different container arrival patterns, and this influence is also related to the container storage cost and the bunker price.

An exact algorithm for inland container transportation network design

In this paper, we investigate the inland depot location problem of the inland transportation system. In inland container transportation, empty containers are transported between depots and consignees/shippers, and empty containers should be repositioned after/before inbound/outbound full containers. We build a robust mathematical model that focuses on determining when and where consignees/shippers are assigned to. In addition, inter-depots empty container repositioning is implemented considering demand uncertainty. This paper proposes a branch-and-price algorithm that is based on Lagrangian relaxation and column generation. We show the optimality condition of the pricing subproblem and construct a simpler formulation in this paper. Computational experiments are performed with test instances that mimic real life. Our results also show that considering time compatibility of full and empty container routes is closer to reality and increases the utilization of empty containers in depots. The proposed algorithm yields promising solutions compared with CPLEX.

Analysis of modal shift potential towards intermodal transportation in short-distance inland container transport

This study investigated modal shift potential in short-distance inland container transport by considering behavioral aspects of inland container transportation mode choice using the stated choice experiment technique. This was applied to one short-distance inland container transportation corridor in Turkey between Denizli region and the seaports of Izmir. The stated choice experiment in this study included two alternatives, intermodal-rail and road transport, as they are the two inland transportation modes available in this transport corridor. These transportation modes were described by five attributes: transportation cost, transit time, delay percentage, frequency and free time. Estimation results show that all five attributes are statistically significant, however, transit time is only statistically significant in the estimations of mixed logit models with random transit time coefficient indicating the preference heterogeneity of the respondents towards the transit time. The elasticities indicate that the transportation cost attribute has the biggest impact on mode choice and the modal shift is more sensitive to the road transport costs than the transportation cost of intermodal rail. The simulations showed that the most effective policy for modal shift towards intermodal rail in the investigated corridor is doubling the train frequency and reducing transit time 50% depending on the increased frequency. The outcomes and methodological approach of the study can provide a framework for developing effective modal shift policies to reduce the high road dependency of inland container transportation in Turkey and other countries. The case-specific approach can also help to identify modal shift policies and practices tailored to the characteristics of applied transportation corridors.

Assessing the Environmental Benefits of Dry Port Usage: A Case of Inland Container Transport in Turkey

Inland transportation of maritime freight conducted by trucks creates extensive emissions. These emissions can be mitigated by using intermodal-rail transport through dry ports. In that regard, this study evaluated the environmental benefits of dry port usage by using discrete event simulation modelling. The results show that the current level of dry port-based intermodal transportation decreases greenhouse gas (GHG) emissions by 5.79% compared to transportation of all containers on the road. Evaluating the impact of the electrified railway line on the GHG emissions revealed unexpected results; the electrification of the railway line would decrease GHG emissions only by 0.06%. The improvements in empty container movement and scheduling slightly reduced GHG emissions by 0.69% and 0.63% respectively, however, highest GHG emissions reduction resulted from modal shift by 6.56%. This study extended the previous literature by assessing not only the environmental benefits of dry port usage but also its effects on train capacity usage, while taking the empty container movement into account.

Effects of demurrage and detention regimes on dry-port-based inland container transport

Increase of congestion at container deep seaports and shortage of capacity has led inland transport systems worldwide to rely more and more on inland terminals, and on the use of high capacity modes of transport to generate economies of scale and reduce negative effects of trucking. In this setting, planning the transport of maritime containers between a deep seaport and a final inland destination must also consider due dates and soft time windows, the latter known as Demurrage and Detention (D&D). In this paper, we formalize the concept of D&D, model the multimodal planning problem, and assess the impact of different D&D regimes on the emerging inland transport systems. By means of an experimental framework, we compare different D&D policies and provide managerial insights. The experiments highlight the effects of existing D&D regimes on transport efficiency and provide guidelines for their choice in practice. D&D are shown to have a twofold effect: first to limit consolidation opportunities and force the use of trucks as buffer, and second to push containers to dwell unnecessarily at the seaports.

Modal choice preferences in short-distance hinterland container transport

Short distance inland container transport to Western European seaports provides opportunities for additional modal shift to intermodal transport, thanks to the concentration of transport flows transported to the immediate hinterland of these ports. The literature on modal choice behavior, however, fails to explain the (relatively low) success of this market segment. In this paper, a choice-based conjoint experiment is conducted to increase the insight on the preferences of modal choice decision-makers in Belgium, active in the considered market segment. The findings of the experiment suggest that, to enhance a further modal shift, operators should try to provide daily services at a competitive price, with a focus on providing more reliable services than road transport. Additional efforts should be made to correctly inform decision-makers on the available intermodal services.

A model for a multi-size inland container transportation problem

In the multi-size Inland Container Transportation Problem (mICT) trucks are able to transport up to two 20-foot or one 40-foot container at a time along routes with various pickup and delivery locations. A mixed-integer linear program for the mICT is presented using two alternative objective functions: minimization of the total travel distance and minimization of the total operation time of the trucks. The presented model is tested on instances which vary in size. Computational experiments show that by means of the presented model small problem instances can be solved optimally.

Evaluating modal shift policies for inland container transport in Korea: a GIS-based approach

Intermodal freight transport has recently gained much attention from researchers as well as policy makers for its environmental sustainability in terms of low energy use and low emissions per ton-kilometre basis compared to truck only transport. This paper presents a framework to develop an intermodal freight transport network based on geographic information system (GIS) for evaluating the effectiveness of potential policies on improving the modal share of rail container transport in South Korea. Modal shift policies evaluated in this paper are nationwide rail subsidy provision, reduction in transhipment time between roads and rail lines, and construction of a new rail facility at Busan Newport. The GIS model allows the analysis of modal competition and congestion effects in the networks due to spatial variation in demand, transport costs, and infrastructure constraints.

A Tabu Search Heuristic for the Inland Container Transportation Problem

The Inland Container Transportation Problem describes the movement of full and empty containers among a number of terminals, depots and customers in a hinterland region. A trucking company with a homogeneous fleet of trucks has to serve customers which either receive goods by inbound containers or ship goods by outbound containers. While keeping given hard time constraints the total operating time of all trucks has to be minimized. A comprehensive mathematical formulation which considers vehicle routing and scheduling and empty container repositioning simultaneously is defined. The problem is solved by an efficient Tabu Search Heuristic. Computational experiments carried out on small- and large-sized instances indicate that the proposed algorithm performs well with respect to effectiveness and efficiency.