Intermodal Container Research Articles

Intermodal freight network incorporating hub-and-spoke and direct calls for the archipelagic Philippines

Compared with point-to-point (PTP) transport, a hub-and-spoke (HS) network benefits from consolidation of cargoes in hubs, leading to lower average costs for hub-to-hub transport because of scale economies. This article explores the use of intermodal road – Roll-on Roll-off (RoRo) transport, in complement with container transport, that is, in a combined HS and PTP network topology for the archipelagic Philippines. The mixed HS network is modeled to incorporate the properties of multiple allocations, non-restrictive networking policy and general hub network topology. The large network problem is solved by a heuristic that uses Lagrangian relaxation as a starting point. The model is able to locate hub ports where cases of intermodal road-RoRo and container transport could transship and be used complementarily. It is shown that considerable savings in total network costs could be realized with a mixed network, as compared with a purely PTP one.

A Decision Support System for Optimizing Operations at Intermodal Railroad Terminals

In this paper, we present a decision support tool to optimize two of the most critical activities in intermodal railroad container terminals, in an iterative and integrated framework devoted to the terminal profit improvement. First, the model allows optimizing the freight trains composition, maximizing the company profit, while respecting physical and economic constraints, and placing in the train head/tail containers prosecuting to subsequent destinations. Hence, based on the resulting train composition, the decision support system allows optimizing the containers allocation in the terminal storage yard, in order to maximize the filling level while respecting physical constraints. The model is successfully tested on a real case study, the inland railroad terminal of a leading Italian intermodal logistics company.

Urban intermodal terminals: The entropy maximising facility location problem

An important problem confronting port cities is where and how to accommodate port growth. Larger ships combined with increased container throughput require more yard space and generate more traffic, straining the urban fabric in the vicinity of the port. A promising solution to this problem is the development of urban intermodal container terminals (IMTs) that interface with both road and rail (or possibly inland waterway) networks. This raises two linked choices; where to locate the intermodal terminals and what will be their likely usage by multiple shippers, each having a choice of whether or not to use the IMT as part of an intermodal transport chain. The use of an IMT by a shipper indicates the shipper's choice of intermodal transport, which comprises a combined use of a high capacity mode (rail or barge between the port and the IMT) and trucks (between the IMT and the cargo origin or destination). The overall problem therefore comprises a mode choice problem embedded within a facility location problem. This paper employs the method of entropy maximisation to combine a logit mode choice model with a facility location model, leading to a non-linear mixed integer programming model. The principal features of the entropy maximising facility location model are illustrated by small and large numerical examples.

Locating urban and regional container terminals in a competitive environment: An entropy maximising approach

Abstract A flexible and policy-oriented model based on the principle of entropy maximisation is proposed for locating competitive multi-user freight facilities in general and inland multi-user intermodal container terminals (IMTs) in particular in a context where multiple users have choices which include whether or not to use the facilities. The overall problem is decomposed into a linked facility location problem (FLP) and a mode choice problem (MCP). The MCP is cast as a three-level nested probability model for determining modal and IMT demands. It was shown that for terminals with sufficiently large handling capacities, the objective function of the overall problem reduces to that of the MCP, the result is a single level mathematical program, which locates facilities to maximise shippers’ expected utility or consumer surplus. The model is suitable for urban or regional planning, but may also be used by terminal operators to estimate shipper demand for given locations. Algorithms for solving the model, principal features of the algorithms and the model are also presented.

Transportation Cost Modeling of Containerized Soybean Exports in the United States

Intermodal container transportation is a growing market for soybean exports in the United States. In an effort to understand the optimal strategies for improving the United States’ economic competitiveness in this emerging market, this research developed a detailed, multi-modal transportation cost analysis model focusing on U.S. soybean container shipments. By using mode-specific transportation network and cost information, the model estimated and compared the “point-to-point” supply chain costs of alternative shipment routes from a domestic production site to a foreign port. For each candidate route, the analysis estimated the transportation time, distance, and cost of each modal segment. This cost analysis model is a building block for a larger research effort that aims to develop strategies to improve freight transportation infrastructure and operations in the context of existing and potential changes in the transportation industry and global market.

A Generalized Stochastic Petri Net Approach for Modeling Activities of Human Operators in Intermodal Container Terminals

This paper proposes a Petri net (PN) representation of the activities performed by the key human operators for unloading/loading containers in an intermodal maritime container terminal (CT) with a low level of automation. These processes are the core of the export, import, and transshipment cycles executed in the terminal. The aim of this paper is to consider both the human component and the material handling resources, e.g., cranes and transporters, by defining an accurate model, which describes how to coordinate humans and use the system resources necessary for serving mother or feeder ships. The developed generalized stochastic PN-based model is of limited complexity and represents a complete, unambiguous, and readable model of the target process before coding it in the target simulation tool. The modular integrated model is tested and validated by the simulation of typical and perturbed scenarios of the Taranto CT, a real terminal that is taken as a case study for its complexity and similarity to CTs with multiple transport modes.

Solving the pre-marshalling problem to optimality with A* and IDA*

We present a novel solution approach to the container pre-marshalling problem using the A* and IDA* algorithms combined with several novel branching and symmetry breaking rules that significantly increases the number of pre-marshalling instances that can be solved to optimality. A* and IDA* are graph search algorithms that use heuristics combined with a complete graph search to find optimal solutions to problems. The container pre-marshalling problem is a key problem for container terminals seeking to reduce delays of inter-modal container transports. The goal of the container pre-marshalling problem is to find the minimal sequence of container movements to shuffle containers in a set of stacks such that the resulting stacks are arranged according to the time each container must leave the stacks. We evaluate our approach on three well-known datasets of pre-marshalling problem instances, solving over 500 previously unsolved instances to optimality, which is nearly twice as many instances as the current state-of-the-art method solves.

Two-stage approach to the intermodal terminal location problem

Multimodal transportation means to transport freight using at least two transportation modes. Intermodal freight transportation, a particular form of multimodal transportation, transports freight in an intermodal container without handling of the freight itself when changing modes. The intermodal terminal location problem involves selecting terminals that constitute an intermodal transportation network and routing freight flows with minimal total transportation and operating costs. Arnold et al. first presented mathematical programming models for the problem. Sörensen et al. recently proposed another model for the problem. However, Lin et al. have shown that the model of Sörensen et al. is complex and time-consuming and therefore developed a modified mixed integer programming model to increase computation efficiency. This study shows that the model of Lin et al. can be further improved by separating the selection of intermodal terminals from the routing of transportation flows. A two-stage programming approach is proposed along with a modified, more efficient matheuristic.

A market-oriented approach for intermodal network optimisation meeting cost, time and environmental requirements

An increasing number of logistics service providers act as freight integrators in offering one-stop solutions to customers in recent years. Most mathematical models of intermodal network design have been developed with a single objective of cost minimisation. This study focuses on developing innovative approaches in the area of enhanced intermodal network design provided by freight integrators. The overall aim of this paper is to demonstrate an original optimisation model that can be employed by freight integrators to address cost minimisation, transit time minimisation, and carbon footprint to better meet market needs. To achieve the aim, this paper develops a bi-objective optimisation model to minimise cost and transit time for the tactical planning of intermodal container flows with constrained carbon emission. The results and analysis of the example of China offer practical insights on the impact of trade-offs between cost and transit time, and the effect of different carbon emission restrictions on intermodal network design.

Intermodal freight transport planning – A receding horizon control approach

This paper investigates intermodal freight transport planning problems among deep-sea terminals and inland terminals in hinterland haulage for a horizontally fully integrated intermodal freight transport operator at the tactical container flow level. An intermodal freight transport network (IFTN) model is first developed to capture the key characteristics of intermodal freight transport such as the modality change phenomena at intermodal terminals, physical capacity constraints of the network, time-dependent transport times on freeways, and time schedules for trains and barges. After that, the intermodal freight transport planning problem is formulated as an optimal intermodal container flow control problem from a system and control perspective with the use of the proposed IFTN model. To deal with the dynamic transport demands and dynamic traffic conditions in the IFTN, a receding horizon intermodal container flow control (RIFC) approach is proposed to control and to reassign intermodal container flows in a receding horizon way. This container flow control approach involves solving linear programming problems and is suited for transport planning on large-sized networks. Both an all-or-nothing approach and the proposed RIFC approach are evaluated through simulation studies. Simulation results show the potential of the proposed RIFC approach.

Using lean principles to drive operational improvements in intermodal container facilities

Purpose – The purpose of this paper is to explore the use of lean principles to drive operational improvements in intermodal container facilities. Intermodal terminals have an important role in today’s globally complex supply networks. In the case of bottleneck-derived terminalization, operational issues such as achieving effective material flow remains a significant and common challenge. To assist with such challenges, the paper develops a conceptual framework built on the principles of lean. Design/methodology/approach – In this paper, a theory-building approach is adopted and a lean terminalization framework developed by combining aspects of lean- and intermodal transport theory with practical insights. The framework was developed in conjunction with two intermodal container facilities within the Scandinavian region. Findings – The conceptual framework demonstrates how lean approaches can be used to identify improvement areas, as well as to develop solutions for improved material flow in the context of intermodal transport operations. The framework can be used to guide the lean implementation process in small to medium intermodal container facilities. Research limitations/implications – The development of the framework represents the first stage of a two-stage project. The second stage will involve implementing and empirically testing the framework in the practical settings of the two-case facilities. Practical implications – Lean is a philosophical approach that consists of a set of principles that drive organizations to continually add value to their operations. The application of lean practices enhances necessary process steps and eliminates those that fail to add value, thereby improving material flow and performance. Social implications – Improving the operational efficiency and effectiveness of container terminals out not only assists the profitability of the facilities but also has flow-on benefits for stakeholders, external customers, consumers and the environment. Originality/value – Lean has been successfully applied in manufacturing because the 1990s, and though it has also found relevance in a number of other industries, applications of lean within the intermodal transport sector is limited.

The Partitioning Min–Max Weighted Matching Problem

We introduce and analyze the Partitioning Min–Max Weighted Matching (PMMWM) Problem. PMMWM combines the problem of partitioning a set of vertices of a bipartite graph into disjoint subsets of restricted size and the strongly NP-hard Min–Max Weighted Matching (MMWM) Problem, that has recently been introduced in the literature. In contrast to PMMWM, the latter problem assumes the partitioning to be given. Applications arise in the field of intermodal container terminals and sea ports. We propose a MILP formulation for PMMWM and prove that the problem is NP-hard in the strong sense. Two heuristic frameworks are presented. Both of them outperform standard optimization software. Our extensive computational study proves that the algorithms provide high quality solutions within reasonable time.

Measurement of particulate matter emissions from in-use locomotives

Particulate matter emissions from a large sample (N = 88) of in-use line-haul freight locomotives were measured in the Alameda Corridor, located near the ports of Los Angeles and Long Beach. Emission factors for black carbon (BC), particle number (PN), fine particulate mass (PM2.5), and lung-deposited particle surface area (LDSA) were computed based on 1 Hz measurements of the rise and fall of particulate matter and CO2 concentrations as the locomotives passed the sampling location. We include LDSA emission factors as relevant for near-source human exposures. Mean emission factors±standard deviations were 0.9 ± 0.5 g kg−1 fuel consumed for BC, (2.1 ± 1.5) × 1016 # kg−1 for PN, 1.6 ± 1.3 g kg−1 for PM2.5, and (2.2 ± 1.7) × 1013 μm2 kg−1 for LDSA. Emission factors for individual trains were slightly skewed, with the dirtiest 10% of trains responsible for 20%, 24%, 28%, and 27% of total BC, PN, PM2.5, and LDSA emissions, respectively. The relative importance of high-emitters is therefore lower for these locomotives relative to previously reported diesel truck emissions. BC versus PN emissions from individual locomotives were found to be anti-correlated, suggesting that the highest emitters of particle numbers are the lowest emitters of black carbon. Using results presented here along with previous measurements, we compared for freight trains versus diesel trucks the amount of BC emissions associated with pulling an intermodal freight container over a given distance. This assumption-dependent comparison showed that in most cases locomotives emit less BC per container hauled than diesel trucks. However, continual decreases in diesel truck BC means that unless emissions from locomotives are decreased in the near future, emissions associated with hauling a container could become lower for diesel trucks than locomotives.

Service network design for an intermodal container network with flexible transit times and the possibility of using subcontracted transport

An intermodal container transportation network is being developed between Rotterdam and several inland terminals in North West Europe: the European Gateway Services (EGS) network. This network is developed and operated by the seaports of Europe Container Terminals (ECT). To use this network cost-efficiently, a centralised planning of the container transportation is required, to be operated by the seaport. In this paper, a new mathematical model is proposed to determine the optimal service schedule between the given network terminals. The model introduces two new features to the intermodal network-planning problem. Firstly, overdue deliveries are penalised instead of prohibited. Secondly, the model combines self-operated and subcontracted slots. The model considers self-operated or subcontracted barge and rail services as well as transport by truck. In a case study of the EGS network, the benefit of using container transportation with intermediate transfers is studied. The results indicate that the propose...

A viral system to optimise the daily drayage problem

The intermodal transport chain can become more efficient by means of a good organisation of the drayage movements. Drayage in intermodal container terminals involves the pick up or delivery of containers at customer locations, and the main objective is normally the assignment of transportation tasks to the different vehicles, often with the presence of time windows. This paper focuses on a new approach to tackle the daily drayage problem by the use of viral system (VS). VS is a novel bio-inspired approach that makes use of a virus-infection biological analogy that is producing very satisfactory results when dealing with complex problems with huge feasibility region.

Impact and relevance of transit disturbances on planning in intermodal container networks using disturbance cost analysis

In North-West Europe, the options for intermodal inland transportation of containers are increasing. Inland corridors become increasingly interconnected in hinterland networks. To minimise operating costs, new methods are required that allow integral network operations management. The network operations consist of allocating containers to available inland transportation services, that is, planning. For adequate planning it is important to adapt to occurring disturbances. In this article, a new mathematical model is proposed: the Linear Container Allocation model with Time-restrictions. This model is used for determining the influence of three main types of transit disturbances on network performance: early service departure, late service departure and cancellation of inland services. The influence of a disturbance is measured in two ways. The impact measures the additional cost incurred by an updated planning in case of a disturbance. The relevance measures the cost difference between a fully updated and a locally updated plan. With the results of the analysis, key service properties of disturbed services that result in a high impact or high relevance can be determined. Based on this, the network operator can select focus areas to prevent disturbances with high impact and to improve the planning updates in case of disturbances with high relevance. The proposed method is used in a case study to assess the impact and relevance of transit disturbances on inland services of the European Gateway Services network.

The Packaging of Efficiency in the Development of the Intermodal Shipping Container

This paper addresses different forms of spatio-temporal ordering in the stowage and handling of cargo on board cargo vessels, as well as docksides. Whilst the introduction of containerisation profoundly altered the urban geographies of many large port cities, as well as devastating the communities built around maritime labour, the core argument developed in this paper concerns the incremental development of spatio-temporal ordering strategies and practices. In particular, it situates the intermodal shipping container within a trajectory reaching back to earlier forms of unitisation such as crates and pallets. In doing so the paper outlines a genealogy of packaged efficiencies, arguing that the central thread linking maritime cargo handling practices in the twentieth century is the unitisation of shape. However, it concludes that the intermodal container achieved global hegemony through the packaged systemic efficiencies of standardisation.

Efficient model and heuristic for the intermodal terminal location problem

A multimodal transportation system transports freight using at least two transportation modes. Among available transportation modes, intermodal freight transportation transports freight in an intermodal container or conveyance without handling the freight itself when changing modes. The locations of intermodal terminals constitute the foundation of an intermodal transportation network. The intermodal terminal location problem therefore aims to determine terminal locations and routes within a transportation network in order to minimize the total transportation and operation costs through collaborations of unimodal road transport and intermodal transport chains. Relevant research includes that of Arnold et al., who first presented mathematical programming models for the problem. Sörensen et al. recently proposed a standard model for the same problem. However, these models are complex and time consuming. Some decision variables and constraints of Sörensen et al.׳s model are proven to be redundant. A modified mixed integer programming model is then developed to increase computation efficiency. The modified model finds more optimal solutions to the benchmark problems than current approaches do, within a reasonable time. Furthermore, two matheuristics are presented to solve the problem more efficiently while obtaining near optimal solutions.

Deep-sea faunal communities associated with a lost intermodal shipping container in the Monterey Bay National Marine Sanctuary, CA

Carrying assorted cargo and covered with paints of varying toxicity, lost intermodal containers may take centuries to degrade on the deep seafloor. In June 2004, scientists from Monterey Bay Aquarium Research Institute (MBARI) discovered a recently lost container during a Remotely Operated Vehicle (ROV) dive on a sediment-covered seabed at 1281m depth in Monterey Bay National Marine Sanctuary (MBNMS). The site was revisited by ROV in March 2011. Analyses of sediment samples and high-definition video indicate that faunal assemblages on the container’s exterior and the seabed within 10m of the container differed significantly from those up to 500m. The container surface provides hard substratum for colonization by taxa typically found in rocky habitats. However, some key taxa that dominate rocky areas were absent or rare on the container, perhaps related to its potential toxicity or limited time for colonization and growth. Ecological effects appear to be restricted to the container surface and the benthos within ∼10m.

Bi-objective optimization of drayage operations in the service area of intermodal terminals

A full truckload vehicle routing problem in drayage operations around intermodal container terminals is studied. Loaded and empty containers need to be transported in a small geographical area. Either the origin or the destination of empty container transports is unknown in advance. The problem is formulated as an asymmetric multiple vehicle Traveling Salesman Problem with Time Windows (am-TSPTW). For the first time, this type of problem is considered from a bi-objective perspective. Three solution algorithms are proposed and compared with each other. Best results are obtained by a two-phase hybrid deterministic annealing and tabu search algorithm.