Control of interacting machines in automated container terminals using a sequential planning approach for collision avoidance

The control of automated container terminals is complex since Quay Cranes (QCs), Automated Guided Vehicles (AGVs) and Automated Stacking Cranes (ASCs) interact intensively for transporting containers, while collision avoidance of equipment must be ensured. This paper proposes a methodology to generate collision-free trajectories of free-ranging AGVs in automated container terminals, while minimizing the makespan of the whole container handling system. A hierarchical control architecture is proposed to integrate the scheduling of interacting machines and trajectory planning of AGVs. Following a so-called overall graph sequence by a scheduler, the collision-free trajectories of AGVs are determined by solving a collection of mixed integer linear programming problems sequentially. Simulation results illustrate the potential of the proposed methodology.     

Storage space allocation in container terminals

Container terminals are essential intermodal interfaces in the global transportation network. Efficient container handling at terminals is important in reducing transportation costs and keeping shipping schedules. In this paper, we study the storage space allocation problem in the storage yards of terminals. This problem is related to all the resources in terminal operations, including quay cranes, yard cranes, storage space, and internal trucks. We solve the problem using a rolling-horizon approach. For each planning horizon, the problem is decomposed into two levels and each level is formulated as a mathematical programming model. At the first level, the total number of containers to be placed in each storage block in each time period of the planning horizon is set to balance two types of workloads among blocks. The second level determines the number of containers associated with each vessel that constitutes the total number of containers in each block in each period, in order to minimize the total distance to transport the containers between their storage blocks and the vessel berthing locations. Numerical runs show that with short computation time the method significantly reduces the workload imbalance in the yard, avoiding possible bottlenecks in terminal operations.     

Bi-objective optimization for the container terminal integrated planning

In this paper, we study the joint optimization of the tactical berth allocation and the tactical yard allocation in container terminals, which typically consist of berth side and yard side operations. The studied two objectives are: (i) the minimization of the violation of the vessels’ expected turnaround time windows with the purpose of meeting the timetables published by shipping liners, and (ii) the minimization of the total yard transportation distance with the aim to lower terminal operational cost. We propose a bi-objective integer program which can comprehensively address the import, export and transshipment tasks in port daily practice. Traditionally, a container transshipment task is performed as a couple of import and export tasks, called indirect-transshipment mode, in which the transit container are needed to be temporally stored in the yard. As the way of transferring containers directly from the incoming vessel to the outgoing vessel, called direct-transshipment mode, has potential to save yard storage resources, the proposed model also incorporates both indirect- and direct-transshipment modes. To produce Pareto solutions efficiently, we devise heuristic approaches. Numerical experiments have been conducted to demonstrate the efficiency of the approaches.     

Green vehicle technology to enhance the performance of a European port: A simulation model with a cost-benefit approach

In this paper, we study the impact of using a new intelligent vehicle technology on the performance and total cost of a European port, in comparison with existing vehicle systems like trucks. Intelligent autonomous vehicles (IAVs) are a new type of automated guided vehicles (AGVs) with better maneuverability and a special ability to pick up/drop off containers by themselves. To identify the most economical fleet size for each type of vehicle to satisfy the port’s performance target, and also to compare their impact on the performance/cost of container terminals, we developed a discrete-event simulation model to simulate all port activities in micro-level (low-level) details. We also developed a cost model to investigate the present values of using two types of vehicle, given the identified fleet size. Results of using the different types of vehicles are then compared based on the given performance measures such as the quay crane net moves per hour and average total discharging/loading time at berth. Besides successfully identifying the optimal fleet size for each type of vehicle, simulation results reveal two findings: first, even when not utilising their ability to pick up/drop off containers, the IAVs still have similar efficacy to regular trucks thanks to their better maneuverability. Second, enabling IAVs’ ability to pick up/drop off containers significantly improves the port performance. Given the best configuration and fleet size as identified by the simulation, we use the developed cost model to estimate the total cost needed for each type of vehicle to meet the performance target. Finally, we study the performance of the case study port with advanced real-time vehicle dispatching/scheduling and container placement strategies. This study reveals that the case study port can greatly benefit from upgrading its current vehicle dispatching/scheduling strategy to a more advanced one.     

A container terminal simulation model with animation capabilities

The objective of this paper is to introduce a computer simulation model with on-screen animation graphics, which can simulate the operations of a container terminal equipped with straddle carriers. The movements of the equipment are simulated as realistically as possible, to include time losses due to the mismatch in the sequence of equipment movements and to traffic congestion. Trucks are normally served in a specified area, but in some cases, straddle carrier drivers can call the truck to be served directly in the container storage areas. The experience of operators is incorporated in the model, in the form of a knowledge base, that is used to simulate the above process and determine the service discipline. The model was designed to evaluate different configurations (changes in yard layout, equipment number and productivity, truck arrival pattern and service discipline) of the simulated system. The proposed model was used to examine the differences between “the observed” operations strategy and the strategy dictated by the operational rules of the port of Piraeus. The results indicate that “the observed” strategy leads to shorter truck service time but increase the traffic conflicts in the terminal's internal transport networks.     

Sequencing twin automated stacking cranes in a block at automated container terminal

In the considered automated container terminal (ACT) that is designed for Shanghai Yangsha Terminal, two automated stacking cranes (ASCs) are configured for each block and they interact with automated lifting vehicles (ALVs) at the two ends of a block individually. To increase the capacity, container yards with multiple rows of blocks perpendicular to the terminal’s shoreline are considered. To utilize the yard spaces, the twin ASCs are devised to share the same tracks installed at the two sides of a block, while interferences between the ASCs challenge the routing and sequencing operations. To isolate the control and simplify the coordination of the two ASCs, the interference between ASCs is formulated by analyzing the minimal temporal intervals between any two tasks. Three models are then established to sequence the container handling tasks under the minimization of the makespan. An exact algorithm and a genetic algorithm are designed to solve the problem. Numerical experiments show that the algorithms are competitive comparing to on-the-shelf solvers. Practical implications are investigated based on the formulations and experimental results. The managerial implications and technological aspects of applying the formulations and algorithms to practical situations to real-world ACTs are discussed.     

Measuring the performance of intermodal freight terminals

As the interface point between road and rail, intermodal freight terminals (IFTs) are critical elements in the total freight distribution chain. This paper addresses the twin objectives of reducing freight transport costs and improving customer service by putting forward a number of indicators designed to measure the performance of IFTs. Each of the three major performance areas, namely customer service, operational efficiency and terminal productivity are discussed in detail.

A methodology is put forward which enables operating strategies to be evaluated. Computer simulation is used in order to arrive at strategies which reduce operating and capital costs and satisfy customer service requirements. The simulation model outputs include performance measures related to customer service such as mean waiting times required for loading and unloading of containers, as well as productivity measures of terminal operations such as lifting equipment utilisation.     

The container retrieval problem with respect to relocation

The demand for container terminal yards is growing significantly faster than the supply of available land; therefore, containers are typically stacked high to better utilize the land space in container yards. However, in the process of container retrieval, non-productive reshuffling may be required to relocate the containers that are stacked on top of the target container. Container retrieval is directly related to the operational efficiency of terminals. Because the industry has become increasingly competitive, it has become critical to introduce a systematic approach to retrieving containers. In this study, we develop a heuristic that can generate feasible working plans for rail-mounted gantry cranes (RMGC) in container yards to minimize the number of container movements while taking the RMGC working time into consideration. The methodology takes into consideration the case that containers are grouped in terms of their retrieval order. Multi-lift RMGC models also are studied. Comprehensive numerical experiments reveal that the method runs faster than other methods published in the literature by several orders of magnitude; additionally, our method is able to solve instances larger than practical use. The number of movements approaches a theoretical lower bound, and the numerical results clearly demonstrate the tradeoff between the number of movements and the working time, and provide useful insights for yard planning.     

Cluster analysis of the competitiveness of container ports in Brazil

The container cargo proportion of total maritime transport increased from 3% in 1980 to 16% in 2011. The largest Brazilian port, the port of Santos, is the 42nd largest container port in the world. However, Santos’ performance indicators are much lower than those of the world’s largest ports, so comparisons with them are difficult. This article focuses on the Brazilian container terminals that handled containers in 2009 and compares port competitiveness. This study classified seventeen Brazilian container terminals into three distinct groups based on the following competitiveness criteria: number of containers handled, berth length, number of berths, terminal tariffs (in US$), berth depth, rate of medium consignment (in containers/ship), medium board (containers/hour), average waiting time for mooring (in hours/ship), and average waiting time for load or unload cargo (in hours/ship). This classification used a hierarchical cluster analysis. The classification shows that the terminal of Tecon in the port of Santos has the best performance of all, while small terminals (<150,000 container units) are the worst performing terminals in Brazil.     

Energy-aware control for automated container terminals using integrated flow shop scheduling and optimal control

The performance of container terminals needs to be improved to handle the growth of transported containers and maintain port sustainability. This paper provides a methodology for improving the handling capacity of an automated container terminal in an energy-efficient way. The behavior of a container terminal is considered as consisting of a higher level and a lower level represented by discrete-event dynamics and continuous-time dynamics, respectively. These dynamics represent the behavior of a large number of terminal equipment. The dynamics need to be controlled. For controlling the higher level dynamics, a minimal makespan problem is solved. For this, the minimal time required by equipment for performing an operation at the lower level is needed. The minimal time for performing an operation at the lower level is obtained using Pontryagin’s Minimum Principle. The actual operation time allowed by the higher level for processing an operation at the lower level is subsequently determined by a scheduling algorithm at the higher level. Given an actual operation time, the lower level dynamics are controlled using optimal control to achieve minimal energy consumption while respecting the time constraint. Simulation studies illustrate how energy-efficient management of equipment for the minimal makespan could be obtained using the proposed methodology.     

Comparative evaluation of resource cycle strategies on operating and environmental impact in container terminals

This paper examines the use of single and dual cycle operations for three types of resources, namely, quay cranes, vehicles, and yard cranes to improve the operating efficiency and reduce the energy consumption in a container terminal. Various cycle strategies are proposed and their corresponding estimation models, describing the stowage distributions of outbound and inbound containers on a ship and the storage sharing level of blocks in the yard, are formulated to estimate the total number of cycles for the resources. Statistical analyses are conducted to evaluate and compare the effect of different cycle strategies on the cycle reductions. From the experiment results, it was found that collaboration between resources with the single cycle operation always outperforms that under the dual cycle operation without collaboration.     

Modeling the cost sensitivity of intermodal inland waterway terminals: A scenario based approach

Cost characteristics of differently sized inland waterway terminals (IWTs) have not received much scientific attention. This observation is remarkable given the importance of costs in transportation decision-making. Classification of differently sized IWTs and their cost structure will lead to more insight into the container cost per terminal. Therefore, the goal of our research was to determine both the characteristics of the cost structure associated with different inland waterway (IWW) container terminal types and the sensitivity of the system to cost/TEU changes in input and operational conditions. We show that terminals with a higher container throughput encounter fewer costs, and can therefore charge a lower price. Assumed delays of 2 h per day on the waterside cause a 4.7–6.6% cost increase per container, mainly caused by extra labor costs. It is also assumed that the changing climate will influence terminal operations and results in extreme water levels (lasting two weeks occurring four times a year) causing a cost increase of 1.0–3.4%. Subsidies can cause cost reductions of 0.3–10.4% depending on the exact form, with the smaller terminals benefiting more because their investment costs are higher relative to operational costs. A subsidy can lower costs by up to 10.4%, but it is questionable whether small and medium terminals will have a lower cost price than the market price, showing that it is important for small and medium terminals to quickly grow in size.     

Scheduling of Intelligent and Autonomous Vehicles under pairing/unpairing collaboration strategy in container terminals

A new class of Intelligent and Autonomous Vehicles (IAVs) has been designed in the framework of Intelligent Transportation for Dynamic Environment (InTraDE) project funded by European Union. This type of vehicles is technologically superior to the existing Automated Guided Vehicles (AGVs), in many respects. They offer more flexibility and intelligence in maneuvering within confined spaces where the logistic operations take place. This includes the ability of pairing/unpairing enabling a pair of 1-TEU (20-foot Equivalent Unit) IAVs dynamically to join, transport containers of any size between 1-TEU and 1-FFE (40-foot Equivalent) and disjoin again. Deploying IAVs helps port operators to remain efficient in coping with the ever increasing volume of container traffic at ports and eliminate the need for deploying more 40-ft transporters in the very confined area of ports. In order to accommodate this new feature of IAVs, we review and extend one of the existing mixed integer programming models of AGV scheduling in order to minimize the makespan of operations for transporting a set of containers of different sizes between quay cranes and yard cranes. In particular, we study the case of Dublin Ferryport Terminal. In order to deal with the complexity of the scheduling model, we develop a Lagrangian relaxation-based decomposition approach equipped with a variable fixing procedure and a primal heuristics to obtain high-quality solution of instances of the problem.     

A generic system dynamics based tool for airport terminal performance analysis

Decision making for airport terminal planning, design and operations is a challenging task, since it should consider significant trade-offs regarding alternative operational policies and physical terminal layout concepts. Existing models and tools for airport terminal analysis and performance assessment are too specific (i.e., models of specific airports) or general simulation platforms that require substantial airport modelling effort. In addition, they are either too detailed (i.e., microscopic) or too aggregate (i.e., macroscopic), affecting, respectively, the flexibility of the model to adapt to any airport and the level of accuracy of the results obtained. Therefore, there is a need for a generic decision support tool that will incorporate sufficient level of detail for assessing airport terminal performance. To bridge this gap, a mesoscopic model for airport terminal performance analysis has been developed, that strikes a balance between flexibility and realistic results, adopting a system dynamics approach. The proposed model has a modular architecture and interface, enabling quick and easy model building and providing the capability of being adaptable to the configuration and operational characteristics of a wide spectrum of airport terminals in a user-friendly manner. The capabilities of the proposed model have been demonstrated through the analysis of the Athens International Airport terminal.     

How do economies of density in container handling operations affect ships’ time and emissions in port? Evidence from Norwegian container terminals

Efficient port services are prerequisites for competitive and sustainable maritime transports. This paper makes advances in studying the determinants of the time that ships spend in port and the associated emissions to air. We estimate a production model for cargo handling based on a unique dataset containing each port of call at the largest container terminals in Norway in 2014. In turn, we use auxiliary engine emission factors to estimate particulate matter and nitrogen oxide emissions from ships at berth, to determine how the corresponding damage costs of air pollution vary with container throughput, location, and terminal investments. We find that Norwegian container terminals operate under increasing returns to density. Small ships that unload few containers are far from reaping economies of density, leading to high marginal time requirements for container handling and consequently high marginal external costs. From a Pigouvian taxation perspective, port charges should therefore be regressive in the number of containers handled. Moreover, we find that the external costs of maritime transports are severely understated when port operations are ignored. Our model allows determining the marginal productivities of port facilities. Thereby, it is instrumental in designing port charges that are diversified according to the quantity of containers handled and the service quality (i.e., the speed of handling operations). Regarding contextual factors, we find that establishing high-frequent liner services improves the ship working rate, while simultaneous calls at a terminal impede productivity. The type of container (loading/unloading; empty/laden) also appears to influence the duration of ship working.     

The impact of job assignment rules for straddle carriers on the throughput of container terminals

Straddle carriers represent a critical resource in the handling of containers within a container terminal. It is essential that they are deployed in an as efficient manner as possible. The research presented in this paper is motivated by the need to critically evaluate job assignment rules for straddle carriers that operate in a multiple straddle environment. This is achieved by developing a discrete event simulation model using industrial simulation software to model a container terminal located in Melbourne, Australia. The model accounts for variables such as the number of straddle carriers needed, the speed of straddle carriers, the arrival rate of trucks, and the job assignment rule. A principal finding of the study is that increasing the number of straddles in the present set‐up from 6 to 7 has a negligible effect on daily throughput. However, an increase in the number of straddles to 7 is expected to have a profound effect on reducing the average waiting time of trucks within the terminal from over 16 minutes to under 9 minutes, a decrease of 46.5%. However, a further increase in the number of straddles results in no further increase in daily throughput. It was observed that the throughput of the terminal is very sensitive to the speeds at which straddles travel. The management of the terminal has proposed a new heuristic job assignment rule for straddles, because the present rule does not assign the jobs to straddles closest to the truck requesting to load or unload a container. As a result a new heuristic job assignment rule was tested. The simulation results revealed that both the old and new rules performed equally well using performance indicators such as average container flow time, daily throughput, average waiting time of jobs, number of jobs in the queue, and straddle utilisation. Therefore, the new rule will not improve these performance measures if implemented     

Foreign participation and competition: A way to improve the container port efficiency in China?

This paper investigates how the involvement of foreign and local ownerships, intra- and inter-port competition and hinterland affect the container terminal efficiency in China and its neighboring countries. The operational efficiency of sample container terminals is estimated by data envelopment analysis, which is followed by regression analysis to examine factors affecting container terminal efficiency. We find that having some Chinese ownership may make a container terminal more efficient, while a container terminal is less efficient with Chinese as the major shareholder. It is also found that intra- and inter-port competition may enhance container terminal efficiency. Finally, the efficiency growth of terminals is examined, and implications for the regional economic disparity in China are discussed.     

In Search of the Link between Ship Size and Operations

Abstract

Since 1990s the liner shipping industry has faced a period of restructuring and consolidation, and been confronted with a continuing increase in container vessel scale. The impact of these changes is noticeable in trade patterns, cargo handling methods and shipping routes, in short ‘operations’. After listing factors influencing size, growth in container ship size is explained by economies of scale in deploying larger vessels. In order to quantify economies of scale, this paper uses the liner service cash flow model. A novelty in the model is the inclusion of +6000-20-foot Equivalent Unit (TEU) vessels and the distinction in costs between single and twin propeller units on ships. The results illustrate that scale economies have been – and will continue to be – the driving force behind the deployment of larger container vessels. The paper then assesses the link between ship size and operations, given current discussions about the increase in container vessel scale. It is found that (a) ship size and operations are linked; (b) optimal ship size depends on transport segment (deep-sea vs. short-sea shipping, SSS), terminal type (transhipment terminals vs. other terminals), trade lane (East-West vs. North-South trades) and technology; and (c) a ship optimal for one trade can be suboptimal for another.     

A study of container berth allocation

This study is based on a major container terminal operator in Hong Kong. Container terminals form a link in the transport chain for transhipment and temporary storage of containers. The service time for vessels including waiting time for berthing must be minimal in order to reduce costs for shipping lines. The use of heuristics and computer simulation to measure different allocation strategies is demonstrated. The existing performance measures of allocation are evaluated and prioritized. Three sets of allocation policies are developed to tackle the day-to-day allocation problems with a view to increasing operational efficiency and enhancing customer service levels. Results show that all three proposed allocation policies have substantial improvements over the existing policy.