Export Containers Research Articles

Analisis Truck Round Time di Lapangan Petikemas Ekspor dalam Kegiatan Receiving di Terminal Petikemas Koja

This research aims to identify the causes of problems or obstacles related to receiving activities, starting from trucks entering the gate-in to leaving the gate-out at the Koja Container Terminal, and providing an understanding of the impacts resulting from the identified problems or obstacles. The research method used is descriptive qualitative, which describes and explains the conditions, phenomena or research variables studied. Truck Round Time analysis at the export container terminal shows that there are several obstacles in the process of receiving containers at the stacking yard. The time of receiving activities can be seen from the length of Truck Round Time, where only 33% of that time reaches the ideal standard, while 67% is still below the ideal standard. The length of time for receiving activities that do not reach ideal standards has negative impacts, such as the potential for congestion inside or outside the terminal, which can harm the good name of the Koja Container Terminal, reduce customer loyalty and satisfaction with the terminal, and hamper other operational processes within. Keywords: Receiving, Container Terminal, Truck Round Time

Reducing Emission Peaks in a Port Terminal through Optimized Truck Arrivals

The reduction of pollutant emissions due to the truck operations in a maritime terminal is the objective of this work. The proposed approach is firstly based on a suitable prediction method developed by the authors and aimed at forecasting the number of trucks reaching the terminal to bring export containers in each day of a specified time interval. Once that the curve of truck arrivals is predicted, an emission model is adopted to evaluate the corresponding pollutant emissions. As a result, it is possible to verify in advance whether at certain days the overall emissions overcome a critical threshold. If this happens, it is needed to redistribute the truck arrivals in order to maintain emissions as close as possible to the threshold. This is optimally done by stating and solving an optimization problem whose solutions are tested in the case study of export flows in the PSA Genova Pra’ (PSA GP) terminal.

Automated rail-water intermodal transport container terminal handling equipment cooperative scheduling based on bidirectional hybrid flow-shop scheduling problem

The importance of rail-water intermodal transport is becoming more and more prominent in recent years. As a key node of rail-water intermodal transportation, the operation efficiency of automated container terminal directly affects the overall transportation efficiency. However, there are few studies on the collaborative scheduling of automated container terminal equipment in rail-water intermodal transportation. Therefore, this paper focuses on the ‘Automated Quay Crane (AQC)-Automated Straddle Carrier (ASC)-Automated Rail Mounted Gantry Crane (ARMG)’ operation system and addresses the operational efficiency requirements of the Automated Rail-Water Intermodal Transport Container Terminal (ARWITCT), Based on the bidirectional Hybrid Flow-shop Scheduling Problem (HFSP), a scheduling optimization model for the ARWITCT is established with the objective of minimizing the maximum completion time. To solve this complex scheduling problem, Particle Swarm Optimization based on Adaptive Tent Chaos Mapping (PSO-ATCM) is designed. In this algorithm, a parameter adaptive adjustment strategy and a Tent Chaos Mapping Optimization Strategy are introduced to help PSO jump out of local optimum. Problem-feature-based encoding and decoding methods are designed for the problem. An ‘insertion-translation’ mechanism is used to judge and resolve the conflicts between import and export containers during the decoding process. The effect of proposed scheduling model and the performance of the proposed algorithm are validated via comprehensive comparison experiments. To validate the effectiveness of proposed scheduling model, we compare the unidirectional HFSP model with the bidirectional HFSP model. The proposed PSO-ATCM is compared with standard Genetic Algorithm, Particle Swarm Optimization algorithm and Adaptive Genetic Algorithm. Computational results demonstrate that the proposed model is effective and PSO-ATCM performs better than other three compared algorithms.

CA 컨테이너를 이용한 수출 멜론의 선도유지 효과

This study investigates the effectiveness of CA (controlled atmosphere) containers in maintaining the freshness of exported melons. The melons were harvested on June 5, 2023, in the Yeongam area of Jeollanam-do, Korea. The CA container was loaded with melon samples packed in an export box. The temperature inside the container was set at 4°C, while the gas composition was set at 5% oxygen, 12% carbon dioxide, and 83% nintrogen. Following two weeks of simulated transportation, quality analysis was conducted at 10°C. The melons were inoculated with spore suspensions, and the decay rate was determined to investigate the effect of the gas composition inside the CA container on suppressing the occurrence of Penicillium oxalicum in melons. The results were compared with a Reefer container set at the same temperature. The samples transported in the CA container exhibited lower weight loss. The melon pulp softening, respiration rate, and ethylene production were slower using the CA container. Moreover, the decay rate during the distribution period in the CA container was lower than in the Reefer container. In contrast, the firmness of melons transported in the Reefer container decreased significantly (from 9.03N to 5.18N) immediately after transportation. The soluble solid content (SSC) of melons transported in the Reefer container also decreased rapidly. The results suggested that the CA container is the optimal export container for maintaining the freshness of melons.

AGV dispatching and bidirectional conflict-free routing problem in automated container terminal

Automated guided vehicles (AGVs) are automated devices that replace internal trucks in container terminals for horizontal container transportation. Compared to internal trucks, AGV has the special characteristic of bidirectional transportation. This characteristic makes AGV change the transport direction without turning around, significantly saving the transport space and time taken up by vehicle transport. However, few studies focus on the bidirectional transportation mode in the AGV scheduling problem to improve the overall efficiency of the automated container terminal (ACT). This study aims at the AGV dispatching and bidirectional conflict-free routing problem. A bi-level mixed integer programming model is proposed, which fully considers equipment coordination, bidirectional conflict-free routing, and import and export container tasks. The bi-level differential evolution algorithm based on the dynamic routing approach is developed to minimize the completion time of all tasks. A series of numerical experiments are conducted to validate the performance of the proposed bidirectional transportation mode and algorithm. The result shows that the efficiency of the bidirectional transportation mode of AGVs is more suitable in the actual ACT operation scenario, and the proposed algorithm can find a better solution within a reasonable amount of time.

Berth template management for the container port of waterway-waterway transit

As one of the most import planning problems in container port operation, the allocation of berth template to all vessels scheduled to call at the port is concerned. This paper investigates the berth template management for container port of waterway-waterway transit, which is different from traditional import and export container ports. Aiming to reduce the container transit distance between the quay side and the yard side, two main evaluation indicators are proposed to maximize the connection between mother vessels and feeder vessels. On this basis, a two-stage mathematical model with four optimization objectives is developed. Numerical experiments are also conducted to validate the effectiveness and efficiency of the proposed method, and scenario analysis also shows the management insights for the container port of waterway-waterway transit.

Towards a Reference Architecture for Cargo Ports

Cyber-Physical Systems (CPS) are physical systems whose operations are coordinated, monitored, and controlled by computing and communication functions. These systems are typically heterogeneous, including Internet of Things and information technology subsystems, and can present a myriad of implementation details, making them very complex systems. An important type of CPS is a maritime container terminal (cargo port), which is a facility where cargo containers are transported between ships and land vehicles for onward transportation and vice versa. A cargo port performs four basic functions: receiving, storing, staging, and loading for both import and export containers. We present here process patterns that describe the functional aspects of cargo ports and a pattern that describes their structural properties (patterns are encapsulated solutions to recurrent problems). These patterns describe semantic aspects found in any cargo port and can be adapted to describe other CPSs. We decompose these process patterns into use cases that describe their interactions with the system. We then integrate the process patterns with structural patterns to assemble a partial reference architecture (RA) that shows the interactions of all the patterns while also indicating the typical stakeholders found in all ports. We validate the proposed reference architecture, highlighting its theoretical and practical value. Software and system designers of cargo ports need to start from a conceptual and abstract view that is subsequently refined to add more details. The use of reference architectures and patterns is an effective way to organize and describe the functional and non-functional aspects of a system, as well as to unify the design of all its aspects. This is, until now, the only published RA for cargo ports, and it can be a useful guideline for the designers of any type of cargo port.

Modeling Categorized Truck Arrivals at Ports: Big Data for Traffic Prediction

Accurate truck arrival prediction is complex but critical for container terminals. A deep learning model combining Gated Recurrent Unit (GRU) and Fully Connected Neural Network (FCNN), is proposed to predict daily truck arrivals using fusion technology. The model can efficiently analyze sequence and cross-section data sets. The new feature in the new model lies in that it, for the first time, incorporates the new parameters influencing traffic volumes such as the vessel-related information, arrival weekdays, and weather conditions into the long-time series of truck arrivals. Furthermore, truck arrivals are predicted in three groups based on their movement purposes: pick-up, delivery, and dual. it also contributes to the literature in a sense that the performance of the model is tested using real big data from a world-leading container port in Southern China. The results generate insightful managerial implications for guiding port traffic management in a generic manner. It reveals the relation of export container arrivals with the Container Yard (CY) closing time of a specific vessel. It is demonstrated the proposed model outperforms the currently available methods with an improved accuracy rate of prediction by 23.44% (dual), 32.09% (pick-up), and 26.99% (delivery), respectively. As a result, the model can better reflect reality compared to the existing ones in the literature. It is also evident that the 3-categorized prediction model can significantly help increase prediction accuracy in comparison with the 2-categorized methods used in practice.

Joint Optimization of Pre-Marshalling and Yard Cranes Deployment in the Export Block

To improve the efficiency of loading operation by researching the optimization of the pre-marshalling operation scheme in the export container block between the time when the ship stowage chart was published and the beginning time of loading, a two-stage mixed integer programming model was established. The first stage established an optimization model of the container reshuffling location, based on the objective function of the least time-consuming operation of a single-bay-yard crane, and designed an improved artificial bee colony algorithm to solve it. Based on the first stage, an optimization model of yard crane configuration and scheduling was built to minimize the maximum completion time of the yard crane in the export block, and an improved genetic algorithm was designed to solve the built model. Through comparative analysis, the performance of our algorithm was better than CPLEX and traditional heuristic algorithms. It could still solve the 30 bays quickly, and the solving quality was 8.53% and 11.95% higher than GA and TS on average, which verified the effectiveness of the model and the science of the algorithm and could provide a reference for improving the efficiency of port operation.

A Stochastic Model for Shipping Container Terminal Storage Management

A good port terminal is not only a major economic multiplier for the nation’s prosperity by being a gateway for trading, but is also an attractor for other commercial infrastructure development such as banks, logistics agencies, and manufacturing and trading investments. A measurement of the efficiency of a terminal is the duration-of-stay of visiting vessels. A quick and efficient loading/unloading process can increase productivity and thus reduce the waiting time for a vessel. In this study, we address the space allocation for stacking export containers. If the storage layout and the loading plan work well together, the productivity of the terminal can be increased and the duration-of-stay needed for each visiting vessel is reduced. In this paper, we propose a hybrid storage policy combining class-dedicated and sharing strategies, and construct a stochastic programming model using the concept of recourse.

VECM을 이용한 화물자동차 운임 결정요인의 실증 분석

In the domestic transportation market, the transportation share of freight cars accounts for 92.6%. In the truck market, real freight rates decreased due to the increase in cost burden due to the increase in prices such as oil prices, and accordingly, overwork, overload, and speeding competition intensified. Accordingly, in 2018, the government implemented a safe fare system as a way to advance cargo transportation and applied it to import and export containers and cement (BCT). Therefore, this study attempted to provide implications for matters to be considered when expanding the safety fare system through time series analysis on the influence of truck fares and various exogenous variables. The research method analyzed the unit root, cointegration test, and VECM of freight rates by tonnage recorded in the actual cargo information network and time series indexes such as domestic economic indicators, industrial indexes, price indexes, and supply indexes. As a result of the analysis, it was confirmed that the exogenous variables affecting the freight rates of each ton class were different, with a positive(+) effect on the whole industry index and import index for trucks of less than 8 tons.

Data-driven dynamic stacking strategy for export containers in container terminals

This study investigates a method for improving real-time decisions regarding the storage location of export containers while the containers are arriving. To manage the decision-making process, we propose a two module-based data-driven dynamic stacking strategy that facilitates stowage planning. Module 1 generates the Gaussian mixture model (GMM) specific to each container group for container weight classification. Module 2 implements the data-driven dynamic stacking strategy as an online algorithm to determine the storage location of an arriving container in real time. Numerical experiments were conducted using real-life data to validate the effectiveness of the proposed method compared to other alternative stacking strategies. These experiments revealed that the performance of the proposed method is robust, and therefore it can improve yard operations and container terminal competitiveness.

Monte Carlo Tree Search algorithm for the receiving containers intelligently problem among container shipping terminals

With the development of economic globalization, shipping exchanges between countries are rapidly increasing and the container throughput of shipping ports has increased quickly, and the operation of most seaport terminals in China has reached a bottleneck which puts forward new requirements for the efficiency of container shipping terminal operations. Therefore, locating for export containers intelligently is of great significance for the development of terminals. This paper focuses on receiving containers intelligently, and establishes the export container locating model based on the principle of actual shipping terminal operations. The Monte Carlo Tree Search algorithm for export container locating problem was proposed and constructed. After examples, the algorithm can effectively solve the problem that meet the constraints, which further proves the practicability of the algorithm and the correctness of the model. The research shows that the method of locating for export container based on Monte Carlo Tree Search algorithm can effectively solve the problem and maintain the green, energy-saving and sustainable development of the shipping terminal. The ideas and methods have certain academic value and reference significance for other NP-Hard problems.

Heuristic/Metaheuristic-Based Simulation Optimization Approaches for Integrated Scheduling of Yard Crane, Yard Truck, and Quay Crane Considering Import and Export Containers

Yard cranes (YCs), yard trucks (YTs), and quay cranes (QCs) are the main material handling equipment (MHE) used to fulfill Yard Storage Plan (YSP) and Vessel Stowage plan (VSP) in a traditional container terminal. However, previous studies have often considered part of these MHE, with either import or export containers being neglected simultaneously. Such studies at most can only achieve local optimality which in a worst-case scenario can cause bottleneck(s) in the downstream operations. In addition, it is noted that the YSP, VSP, and their constraints have been often neglected in previous studies. Such negligence can cause operational problems. To best operate a container terminal, it needs to address the above issues. Our literature review shows that exact methods have difficulty solving a problem of big size to optimality due to NP-hard, thus alternative approaches are still required. Simulation-based optimization approaches are found with the potential to deal with container terminal problems. However, software for the integration of simulation and optimization effectively is found unavailable. In this research, different simulation-based optimization approaches, based on a simulation-based optimization framework (HSBOF), have been developed. These approaches help to schedule YCs, YTs, and QCs in handling both import and export containers for a ship in a traditional container terminal, taking YSP, VSP, and their constraints into consideration. Various heuristics/metaheuristics have been employed in the HSBOF as a sequencing method to arrange alternative operational sequences of containers. The results show that the Simulation(ISFLA) has the best performance.

Container Freight Rates and International Trade Causality Nexus: Evidence from Panel VAR Approach for Shanghai and ASEAN‐6 Countries

Container shipping drives the development of international trade, yet previous studies have not fully appreciated the possible bidirectional causal relationship between container freight rates and international trade. In the context of the “twenty‐first Century Maritime Silk Road,” we use data on export container freight rates and import/export data from Shanghai to ASEAN‐6 countries (Singapore, Vietnam, Thailand, Philippines, Malaysia, and Indonesia) from February 2017 to January 2020 and apply a panel VAR to explore the relationship between maritime transport costs and international trade in the container shipping market. We use the freight rate data are from the Southeast Asia Freight Index, which is used for the first time in an empirical study. The quality and reliability of the freight rate data allow this paper to better identify causal relationships. The results of the panel Granger causality test and the orthogonal impulse response function suggest a bidirectional causal relationship between freight rates and export trade; to further explain, an increase in export trade lowers export freight rates, but an increase in export freight rates hinders export trade, and a growth in import trade unidirectionally raises export freight rates. We believe that international trade may impact freight rates through economies of scale and trade imbalances.

VALUE STREAM MAPPING OF OCEAN IMPORT CONTAINERS: A PROCESS CYCLE EFFICIENCY PERSPECTIVE

International cargo transportation is majorly dependent on marine transport, which moves 80% of the international cargo. With the increase in vessel size and the same yard area available for container transportation, it is important to study the processes and understand the efficiency of the container operations process. This research paper aims to review the import container transportation process and understand the process cycle efficiency through lean six sigma concepts. The process is evaluated from the operations process perspective and documentation process at one of the ports of India. The research has been designed by conducting an industry expert review on the process of container transportation from vessel berthing to gate out for import containers, utilising lean six sigma principles such as value stream mapping (VSM) and process cycle efficiency. The results have contributed to the existing knowledge in identifying the waste in the container handling process and demonstrated the inefficiency in the system from the perspective of waiting time of containers due to customs examination, scanning, and inter-terminal handling and movement. The process cycle efficiency of 40% is calculated by analysing the detailed time of handling containers from vessel berthing to gate out. A new future value stream mapping is proposed considering the process cycle efficiency. Future studies will focus on studying this process for export containers and benchmarking the results with the top-performing ocean ports globally.

Review on the Prices of Shipment Keep Rising in Perspective of Global Shipping Supply Chain Disruption

The global spread of the pandemic has led to the stop of various industries, the shutdown of enterprises, the unemployment of workers and other problems. Recently, one of the issues that have aroused widespread global concern is the problem that the international shipping prices represented by the trans Pacific route continuously rising. This is the apparent performance of the global shipping supply chain interruption and brings interruption to the global supply chain. International shipping is a barometer of the international economic. The reasons behind the sharp rise in shipping prices are complex and diverse. The labor shortage under the pandemic is the root cause of low operation efficiency. The serious shortage of export containers in Asia is the direct cause of demand exceeds supply. The imbalance of international trade is the internal reason for the increase in demand. In addition, there are additional reasons such as the congestion accident in Suez Canal. In order to deal with this situation, each governments use policies, decrees and other measures to intervene moderately on the basis of the market power to restore balance for hoping to recover as soon as possible. But some international organizations related to this issue hold the opposite attitude. Shipping operators have interests directly relevant should reasonably dispatch all available transport capacity to meet demand, rationally treat and make use of short-term high profits and actively cooperate in the face of national survey, review and supervision. The problem of global shipping supply chain interruption needs to be solved jointly by all parties and strengthen pandemic control then solve the problem from the source, to release the delayed transportation efficiency as soon as possible to restore the global shipping supply chain and promote the recovery of the world economy.

Joint Scheduling of Yard Crane, Yard Truck, and Quay Crane for Container Terminal Considering Vessel Stowage Plan: An Integrated Simulation-Based Optimization Approach

The joint scheduling of quay cranes (QCs), yard cranes (YCs), and yard trucks (YTs) is critical to achieving good overall performance for a container terminal. However, there are only a few such integrated studies. Especially, those who have taken the vessel stowage plan (VSP) into consideration are very rare. The VSP is a plan assigning each container a stowage position in a vessel. It affects the QC operations directly and considerably. Neglecting this plan will cause problems when loading/unloading containers into/from a ship or even congest the YT and YC operations in the upstream. In this research, a framework of simulation-based optimization methods have been proposed firstly. Then, four kinds of heuristics/metaheuristics has been employed in this framework, such as sort-by-bay (SBB), genetic algorithm (GA), particle swarm optimization (PSO), and multiple groups particle swarm optimization (MGPSO), to deal with the yard crane scheduling problem (YCSP), yard truck scheduling problem (YTSP), and quay crane scheduling problem (QCSP) simultaneously for export containers, taking operational constraints into consideration. The objective aims to minimize makespan. Each of the simulation-based optimization methods includes three components, load-balancing heuristic, sequencing method, and simulation model. Experiments have been conducted to investigate the effectiveness of different simulation-based optimization methods. The results show that the MGPSO outperforms the others.

Flexible yard management in container terminals for uncertain retrieving sequence

With the booming traffic of global container transport, the container port throughput keeps increasing too. As the key node of the maritime network, the handling efficiency of container terminal always determine the efficiency of the whole container transport. In order to improve the handling efficiency of the container terminal, the optimization of yard space is still a challenge for terminal manager. Generally, the whole export block is used to be separated into several clusters to store export containers for different loading liners. In former studies, the unit of template generated is always fixed clusters like subblock, and the concept of flexible loading cluster is seldom touched. The application of flexible loading cluster, where the number of bays, rows and tiers can be changed based on service requirement, is discussed in this research. Thus this study wants to find out the optimal choice of flexible loading clusters and better solutions for export container allocation. A bi-objectives model which considers both the transportation distance and the handling congestions is built. A heuristic approach is developed to solve the real-life cases. We emphasize the possible rehandles during loading process and it is concluded that the application of flexible loading clusters is efficient for uncertain retrieving sequence.

The block relocation problem with appointment scheduling

In many container terminals, containers are piled vertically and horizontally in the terminal yard, limited mainly by the dimensions of the yard crane. Import and export containers are typically stacked separately. An external truck can access the terminal to pick up an import container only after making an appointment reserving a pickup time. To reduce truck waiting time inside the terminal, container pickup appointments are normally scheduled on a time window basis. However, when a truck arrives at the terminal yard at the appointed time, it is common for the target container not to be at the top of its stack, resulting in unproductive relocations to remove all the containers stacked above the target container and thus increasing the truck's waiting time. To minimize the number of relocations, the Block Relocation Problem (BRP) is usually solved independently, without consideration of appointment scheduling. In this paper, we introduce a new optimization problem—the Block Relocation Problem with Appointment Scheduling (BRPAS)—to jointly address the two issues. To solve the problem, two binary IP models are proposed, and examples from the literature are solved to confirm the performance of the two models. The proposed formulations are further extended to cover several operational aspects related to the flexibility of container pickup operations. Results show that the proposed approach can improve container relocation operations at terminal yards by coordinating with appointment scheduling.