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Since the first automated container terminal (ACT) was introduced at Europe Container Terminals Delta Terminal in Port Rotterdam back in the year 1992, a lot of research had been done to improve the management of ACT. However, up until recently, the number of literature available still appeared scarce. Hence, this paper aims to review the collection of literature about ACT to generate an exhaustive summary to answer the formulated review question in this study.

Preferred reporting items for systematic reviews and meta-analyses to narrow down the search parameters of literature retrieved so that only relevant articles were only selected. The systematic literature reviews were applied to analyse the content of the articles retrieved to determine its journal ranking, research findings and timeline of publications.

The adoption of ACT technology by container terminal operators could increase the terminal efficiency in productivity, cost reduction and environmental sustainability. Owing to global environmental awareness, the research trend of container terminal field and container terminal operator in the terminal design is much more environmentally friendly oriented.

The limited numbers of experts in the management of ACT are causing challenges in data collections.

The analysis of the global ACT trend could help academicians and industrial investors to review the revolution timeline of maritime technology in port and shipping that is happening rapidly.

The analysis of timeline and collective literature leads to the propose of the conceptual framework to determine the relationship between increased productivity, cost reduction and environmentally sustainable.

Magnet spot is the primary method to develop the automated guided vehicle (AGV) guidance system for many automated container terminals (ACT). Aiming to improve the high flexibility of AGV operation in ACT, this paper aims to address the problem of technical stability leading to ACT production paralysis and propose a mini-terminal AGV robot for testing laser simultaneous location and mapping (SLAM)-based methods in ACT operation scenarios.

This study developed a physical simulation robot for terminal AGV operations, providing a platform to test technical solutions for applying laser navigation-related technologies in ACTs. Then, the terminal-AGV navigation system framework is designed to apply the laser-SLAM-based method in the physical simulation robot. Finally, the experiment is conducted in the terminal operation scenario to verify the feasibility of the proposed framework for lased-SLAM-based method testing and analyze the performance of the different mini-terminal AGV robots.

A series of experiments are conducted to analyze the performance of the proposed mini-terminal AGV robot for laser-SLAM-based method testing. The experimental results show the validity and effectiveness of the AGV robot and AGV navigation system framework with better local map matching, loopback and absolute positional error.

The proposed mini-terminal AGV robot and AGV navigation system framework can provide a platform for innovative laser-SLAM-based method testing in ACTs applications. Therefore, this study can effectively meet the high requirements of ACT for maturity and stability of the laser navigation technical.

The purpose of this paper is to propose a model that determines the strategy of owning and renting trucks in combinations with internal truck scheduling and storage allocation problems in container terminals.

To deal with this complicated problem, a two-level heuristic approach is developed, in which the integration problem is decomposed into two levels. The first level determines the daily operations of the internal trucks, while the second level determines the truck employment strategy based on the calculation in the first level.

The results show that: even if the using cost of owned yard trucks is much lower than the cost of rented yard tucks, terminal companies should not purchase too many trucks when the purchasing price is high. In addition, the empirical truck employment strategies, which are purchasing all the trucks or renting all the trucks, are not cost-effective when compared with the proposed yard truck employment strategy.

The paper provides a novel insight for the internal truck employment strategy in container terminals which is the determination of the strategy of employing renting and outsourcing yard trucks to meet operational daily transportation requirements and minimize the long-term cost of employing yard trucks. A mathematical model is proposed to deal with the practical problem. Also, this study presents better solution than empirical method for employing different types of yard truck. Thus, in order to obtain more benefit, terminal companies should employ the proposed yard truck employment strategy.

Seaports are a signifier for the world economy and international trade. Notwithstanding the considerable role of Chinese ports in global trade, only few studies have explored the efficiency of Chinese container terminals. Furthermore, studies on Chinese port efficiency has typically centered on port-level analysis, not terminal level. Therefore, this study aims to examine the operation efficiency of Chinese container terminals.

This study uses super-efficiency data envelopment analysis (SE-DEA) approach. SE-DEA is superior than basic DEA model because it is feasible for categorizing and ranking the efficiency of container terminals more accurately and comprehensively. In the basic model, if the several decision-making units (DMUs) are efficient, the efficiency value of them is “1.” However, in the SE-DEA model, the most efficient DMU is over “1.” Based on the level of container throughput in 2018, the top 20 Chinese container terminal companies were selected. Various production quotas were selected as inputs, while the container throughput was considered output.

The findings show that Terminal Shanghai Mingdong Container Terminal Co., Ltd. was ranked 1, followed by Shanghai Shengdong International Container Terminal Co., Ltd., Shanghai International Port (Group) Co., Ltd. and Yidong Container Terminal Branch.

This study contributes to providing some insights into Chinese container terminal industry to augment the efficiency. This study also provides practical and policy implications (e.g. better terminal operations) for container terminals.

The purpose of this paper is to evaluate the functioning of the main Spanish and Portuguese containers ports to observe if they are operating below their production capabilities.

To achieve the above-mentioned objective, one possible method is to calculate the data envelopment analysis (DEA) efficiency, and the scale efficiency (SE) of targets, and in order to consider the variability across different samples, a bootstrap scheme has been applied.

The results showed that the DEA bootstrap-based approach can not only select a suitable unit which accords with a port’s actual input capabilities, but also provides a more accurate result. The bootstrapped results indicate that all ports do not need to develop future investments to expand port infrastructure.

The proposed DEA bootstrap-based approach provides useful implications in the robust measurement of port efficiency considering different samples. The study proves the usefulness of this approach as a decision-making tool in port efficiency.

This study is one of the first studies to apply bootstrap to measure port efficiency under the background of the Spain and Portugal case. In the first stage, two models of DEA have been used to obtain the pure technical, and the technical and SE, and both the input-oriented options: constant return scale and variable return scale. In the second stage, the bootstrap method has been applied in order to determine efficiency rankings of Iberian Peninsula container ports taking into consideration different samples. Confidence interval estimates of efficiency for each port are reported. This paper provides useful insights into the application of a DEA bootstrap-based approach as a modeling tool to aid decision making in measuring port efficiency.

Empty container trucks may cause a deficit in transport capacity and contribute to congestion and emissions in the port territory. Reengineering of the container truck hauling process to introduce truck-sharing arrangements using the truck appointment system has the potential of reducing the number of empty-truck trips. The paper aims to discuss these issues.

This research evaluates the results from an investigation of the truck appointment system using a case study approach. The data collection phase involved primary and secondary sources along with using publicly available data on port operations.

The study explores a dynamic truck-sharing facility for a computer-based matching system to assign probable export containers to available empty slots of a container truck. The proposed model reengineers the truck appointment system with a potential to reduce the number of empty-truck trips to increase container transport capacity around seaport gates.

Due to continuous increases in container-freight traffic, leading seaports of the world are experiencing a capacity shortage resulting in traffic congestion. The research findings are useful in practice as the proposed truck-sharing model can be introduced to enhance capacity in the container transport chain of the port territory.

The empty-trucks problem has not been addressed much in studies from a decentralized perspective where all truck operators have an equal chance to contribute to optimize the supply chain in contrast with the typical one-company-based optimization. The solution addressed here uses the shared-transportation concept to cover the research gap.

Conventionally, shipping companies have invested in large ships to achieve economies of scale. More recently, high speed ships have been proposed as a means of achieving timely service for customers and improving shipping performance. Yet another solution offered here is to boost the cargo handling speed at port allowing for a higher number of annual round trips. Both the cost efficiency and timeliness of shipping service can be improved. The economic trade‐offs between the investments in cargo handling and ship propulsion technologies are formally analysed by taking the round trip frequency as the key to performance. The theoretical analyses as well as the practical cases studied indicate that investments in cargo handling technology, such as automation of container terminal operations and hatchless self‐loading ships, have indeed considerable profit‐making potential for shipping companies. Other technology investment opportunities appear less promising: ship propulsion due to energy consumption and environmental concerns; and larger ships due to low customer responsiveness and risks of low capital productivity.

The use of queueing network models was stimulated by the appearance (1975) of the exact product form solution of a class of open, closed and mixed queueing networks obeying the local balance principle and solved, a few years later, by the popular mean value analysis algorithm (1980). Since then, research efforts have been produced to approximate solutions for non-exponential services and non-pure random mechanisms in customer processing and routing. The purpose of this paper is to examine the suitability of modeling choices and solution approaches consolidated in other domains with respect to two key logistic processes in container terminals.

In particular, the analytical solution of queueing networks is assessed for the vessel arrival-departure process and the container internal transfer process with respect to a real terminal of pure transshipment.

Numerical experiments show the extent to which a decomposition-based approximation, under fixed or state-dependent arrival rates, may be suitable for the approximate analysis of the queueing network models.

The limitation of adopting exponential service time distributions and Poisson flows is highlighted.

Comparisons with a simulation-based solution deliver numerical evidence on the companion use of simulation in the daily practice of managing operations in a finite-time horizon under complex policies.

Discussion of some open modeling issues and encouraging results provide some guidelines on future research efforts and/or suitable adaption to container terminal logistics of the large body of techniques and algorithms available nowadays for supporting long-run decisions.

An integrated queueing network focused on container storage/retrieval operations occurring on the yard of a transshipment hub is proposed. The purpose of the network is to support decisions related to the organization of the yard area, while also accounting for operations policies and times on the quay.

A discrete-event simulation model is used to reproduce container handling on both the quay and yard areas, along with the transfer operations between the two. The resulting times, properly estimated by the simulation output, are fed to a simpler queueing network amenable to solution via algorithms based on mean value analysis (MVA) for product-form networks.

Numerical results justify the proposed approach for getting a fast, yet accurate analytical solution that allows carrying out performance evaluation with respect to both organizational policies and operations management on the yard area.

Practically, the expected performance measures on the yard subsystem can be obtained avoiding additional time-expensive simulation experiments on the entire detailed model.

As a major takeaway, deepening the MVA for generally distributed service times has proven to produce reliable estimations on expected values for both user- and system-oriented performance metrics.

This research uses an optimisation model, based on the Six Sigma methodology, which assists marine container terminal operators to minimize trucks' congestions, as a defect in the global containerisation and smoothing the gate activity to reduce trucks' turn‐around times. The main purpose of this paper is implementing the Six Sigma in the landside of marine container terminals to reduce the average number of trucks in queues and average trucks' waiting times in both entrance and exit gates.

This study examines the applicability of the DMAIC method along with the SIPOC, cause and effect diagram, and failure mode and effect analysis (FMEA).

In this paper, Six Sigma methodology is found as an accurate optimisation tool in marine container terminals. Risk Priority Numbers obtained from the FMEA analysis denote that additional control procedures and associated inspections are needed as monitoring tools on the working time and activity of weighbridge operators and truck's drivers. In addition, serious consideration should be given to operator's performance appraisal and improving the administrative systems.

This study was carried out with some boundaries; like the complex operational system in marine container terminals, available data, time constraints, training the team members and controlling the implemented obtained results.

To date, no study has adequately examined the Six Sigma methodology in marine container terminals as an optimisation tool for reducing trucks' congestion. The challenging issues inherent this problem and the limitation of existing research, motivates this study.