Port Container Terminals Research Articles

Port Risk Management in Container Terminals

Abstract World trade increasingly relies on longer, larger and more complex port systems, where maritime transportation is a vital backbone of such operations. Port systems are more prone to being risk oriented. Many specific methods have been found to assess risk and safety in a port area or operation. A review is presented of different approaches to quantify the risk in port area. On the other hand, there is no specific risk management method or framework to cope with threats and hazards as a whole. This conceptual paper presents a Port Risk Management (PRM) methodology, seeking to transfer the safety-oriented Formal Safety Assessment (FSA) framework into the domain of port container terminal. The PRM methodology, has been developed to model all the probable port risks, by taking into account its different factors and their mutual influences. This paper presents a risk management methodology into the domain of port container terminals. This methodology constitutes a decision support framework that will be used to conduct port to port risk evaluations or to assess a whole port’s and terminal’s overall risk level in order to facilitate continues improvement strategies. An empirical study is contacted in order to provide evidence for risk management at the port container terminals in Greece. There is a need for methodologies and tools for assessing and managing the overall risk in maritime and port operations, which are increasingly complex and are dependable by systematic and nonsystematic risks. The critical impact on a number of port stakeholders has established a new methodology and a port risk index a considerable task.

La eficiencia de los puertos en la región del APEC, 2005-2013: una medición a través del Análisis de la Frontera Estocástica (SFA)

This paper presents a model using the Stochastic Frontier Analysis to measure the efficiency of container terminals in the main ports of Asia-Pacific Economic Cooperation for the period 2005-2013. Efficiency is calculated through the estimators: JLMS (Jondrow, Lovell, Materov & Schmidt, 1982) and BC (Batesse & Coelli, 1988). It was used as inputs quay length and employed personnel and for output teus annually moved. The scores showed that in the period analyzed, any port was efficient on average, while Shanghai was the one who presented the highest results, in contrast to the port of Callao in Peru, whose efficiency levels were the lowest.

An Empirical Study on the Efficiency of Container Terminals in Russian and Korean Ports using DEA models

The steady growth of seaborne trade has resulted in the further development of container ships, ports, and container terminals, and the operating efficiency of a container terminal is a decisive element for its competitive ability in international markets. The aim of this research is to evaluate the relative efficiency of Russian and South Korean container terminals. For this purpose, the output-oriented DEA was applied to 31 container terminals of Russian and South Korean seaports for the years from 2012 to 2014. The results indicate that Korean container terminals exhibited higher efficiency scores than their Russian counterparts.

Approximate the scheduling of quay cranes with non-crossing constraints

In port container terminals, the scheduling of quay cranes (QCs) for a container vessel is one of the most critical operations. This paper investigates the problem of scheduling quay cranes with non-crossing constraints, wherein QCs cannot cross over each other because they are on the same track. The objective is to minimise the makespan of a container vessel, which is the latest completion time among all handling tasks of the vessel. Compared with several 2-approximation algorithms in the literature, this paper presents an approximation algorithm with a worst case ratio 2−2m+1<2 for any m QCs. This ratio is demonstrated to be the best possible among all partition-based algorithms in the literature. Besides, we study the scheduling of two quay cranes with different processing speeds. For an arbitrary speed ratio s ≥ 1, an approximation algorithm with worst case ratio (1+s)21+s+s2 is provided.

Data envelopment analysis of AGV fleet sizing at a port container terminal

A decision-making approach based on Data Envelopment Analysis (DEA) for determining the efficient container handling processes (considering the number of employed Automated Guided Vehicles (AGVs)) at a port container terminal (PCT) is presented in this paper. Containers are unloaded from the ship by quay cranes and transported to the storage area by AGVs. We defined performance measures of proposed container handling processes and analysed the effects when changing the number of AGVs. The values of performance measures were collected and/or calculated from simulation. Container handling process, with a fixed number of quay cranes, when a different number of AGVs is used to transport containers from berth to assigned locations within storage area, represents a decision-making unit (DMU). We applied the basic CCR (Charnes, Cooper and Rhodes) DEA model with two inputs: average ship operating delay costs and average operating costs of employed equipment at a PCT, and two outputs: average number of handled import containers per ship and weighted average utilisation rate of equipment at a PCT. DEA method proved to be useful when testing different DMUs and when determining efficient DMUs for planning purposes. This study shows that efficiency evaluation of AGV fleet sizing and operations is useful for planning purposes at PCTs.

Development of priority rules for handlings in inland port container terminals with simulation

A container terminal is a complex system with many subsystems, for example stacking area, cranes and vehicles, and a large number of decisions for each subsystem. Due to the interactions of these subsystems, there is a lot of stochastic influence and interdependencies within the decisions, which make an optimized operation of a whole container terminal very complex and without technical and methodical support hard to handle. One optimal operated subsystem influences all other subsystems and therefore does not result in an optimality for the whole system. To optimize the operations in an overall system with all its stochastic influence and interactions the method of simulation is used in this paper, which provides the opportunity to create an experimental model and identify the best recommended course of action. The Institute of Transport Logistics developed the simulation suite ContSim, which permits the modelling and simulation of material and information flows in a container terminal. ContSim provides the possibility to model a terminal on a microscopical layer. All handling and controlling processes of the terminal can be modelled and parameterized.

Container relocation problem with time windows for container departure

The blocks relocation problem is a classic combinatorial optimisation problem that occurs in daily operations for facilities that use block stacking systems. In the block stacking method, blocks can be stored on top of each other in order to utilise the limited surface of a storage area. When there is a predetermined pickup order among the blocks, this stacking method inevitably leads to the reshuffling moves for blocks stored above the target block and the minimisation of such unproductive reshuffling moves is of a primary concern to industry practitioners. A container terminal is a typical place where this problem arises, thus the problem being also referred to as the container relocation problem. In this study, we consider departure time windows for containers, which are usually revealed by the truck appointment system in port container terminals. We propose a stochastic dynamic programming model to calculate the minimum expected number of reshuffles for a stack of containers which all have departure time windows. The model is solved with a search-based algorithm in a tree search space, and an abstraction heuristic is proposed to improve the time performance. To overcome the computational limitation of exact methods, we develop a heuristic called the expected reshuffling index (ERI) and evaluate its performance.

Development of Models Predicting Dwell Time of Import Containers in Port Container Terminals – An Artificial Neural Networks Application

The general aim of this paper is to propose the development of a methodological framework that incorporates the various factors affecting the Dwell Time (DT) of containers in container terminals. Container terminals are regarded as a key element of logistics chains since they are a link between sea and the hinterland transportation modes. Workload forecasting is essential when it comes to truck arrivals for the avoidance of bottlenecks and the smooth integration of container terminals in the supply chain. Terminal operators, tend to make stacking decisions based on mostly on factors suc the container's weight, size and type. The suggested methodology requires the collection of aggregate data and the application of Artificial Neural Networks (ANN) to identify the determinants of Dwell Time (DT). The first results of the ANN showed that the most important factors affecting significantly the model's accuracy are the following: containers size and type, the day and month of the container's discharge, the vessel's port of origin and the commodities transported.

Productividad total de los factores en las terminales de contenedores en los puertos de México: una medición a través del índice Malmquist

This paper presents an analysis of change in the Total Factor Productivity (TFP) of container terminals in major ports in Mexico in the period 1982-2010. For this, we propose Malmquist Index, which decomposing the change in productivity in two factors: Change in efficiency (catch-up effect) and technological change (shift frontier). The results show that in general there was an increase in productivity over the period analyzed, which is explained by technological change; Manzanillo was the port that had higher growth in productivity, and opposite Tuxpan was the one who had the greatest reduction, it was due mainly for the negative trend in traffic mobilized during containers. These results show the need to develop public policies for ports to operate at maximum capacity.

Automation in Port Container Terminals

This paper introduces the concept of automation and port container terminals and addresses some general considerations vis-à-vis automation in this type of port facilities. It further advances current knowledge on this topic by introducing an automation philosophy that adapts the implementation of automation technologies currently available on the market to the particular needs of each PCT. Finally, it concludes by summarising the main advantages and challenges regarding the automation of PCTs.

The Artificial Neural Networks to Obtain Port Planning Parameters

Artificial Neural Networks can be a great help in port planning activity. Bad planning might lead to an incorrect use of the available resources and means.This research is focused on neural networks’ behavior analysis within the port planning process, in the context of containers terminals, more precisely to study the possible traffic growth and the requirements in terms of equipment and installations. The traffic levels in these terminals and the minimum necessary investment can be thus evaluated with no need or with just a very low new investment.The methodology shows the fundamentals of the Artificial Neural Networks application and the considered sequence to develop the container port terminals planning, supported by the MATLAB code tools.The article reaches finally the conclusion that both the tool and the proposed methodology can be considered as acceptable to perform this kind of planning forecasts and to be used in the future.The results seem to show that the ANN can be used to model port planning issues linked to container terminals, based on historical data series.

Improvement in Queuing Network Model to Reduce Waiting Time at Berthing Area of Port Container Terminal via Discrete Event Simulation

Queuing problems present a gap in the availability of knowledge at port container terminals. This study is focused on various types of services for port container terminal queuing system. The purpose of this paper is to introduce a methodology to decrease waiting time without any reduction in productivity. A new approach for servicing at the queue is proposed, and with this idea waiting time will be reduced without any change in productivity or additional cost. To execute this approach in a port container terminal, berthing areas of the port are simulated with ARENA 13.5, and this new approach is implemented in the model. The result of this change are compared with results of a port container terminal as case study. With implementing this method the waiting time is reduced dramatically and productivity increased slowly.

Centralization or decentralization: A comparative analysis of port regulation modes

This paper studies the comparison of two kinds of port regulation modes – the centralization mode and the decentralization mode – using principal-agent theory and dynamic game theory. The optimal tariffs, port capacities and port efficiency levels under these two regulation modes are determined. The theoretical results are applied to the container terminals in Port of Shanghai in China. Sensitivity analysis and comparative studies show that the tariff, port efficiency level, port service demand and social welfare are higher under the decentralization mode, while the impact to port capacity and port operator’s profit with different port regulation modes is uncertain.

Layout analysis affecting strategic decisions in artificial container terminals

As a result of a major growth in world trade, importance of the container terminals, which are the exit gates of international maritime trade, has been emphasized and the competition between these terminals has increased. In recent years, increasing competition in shallow seas, which have low berth depth and intensive trade, has caused terminal managers to investigate how the strategic decisions affect the future development of terminal operations. Due to their low berth depth, container terminals in the feeder ports of shallow seas are built artificially near coastlines. The most common layouts found in these terminals are Π, L, π, or Ψ. In this paper, simulation models were developed for the container terminals to examine the effect of transporter dispatching rules and resource allocation strategies in terms of total annual handling amount. According to the results, terminal performance is significantly affected by terminal layout design under different transporter dispatching rules and allocation strategies.

Scheduling small number of quay cranes with non-interference constraint

Quay crane (QC) scheduling significantly affects the turn-around time of a container vessel, and it plays an important role in container terminal operation. Lee et al. (An approximation algorithm for quay crane scheduling with non-interference constraints in port container terminals, Presented at Tristan VI, Phuket, June 10–15, 2007) present a 2-approximation algorithm for QC scheduling problem with non-interference constraint. In this paper we revisit Lee’s heuristic for the scenario with small number of QCs, and prove that it is 4/3 and 5/3-approximation for the case with two QCs and the case with three QCs respectively.

Rationalization of servicing reefer containers in sea port area with taking into account risk influence

Abstract This paper is aimed at presentation of a set of methods for rationalization of servicing containerized refrigerated cargoes in sea ports. During servicing reefer containers in port container terminals, take place various combinations of risk factors which can lead to loss of quality merits of cargoes contained in them. In the paper the risk factors capable of influencing quality of cargoes during their servicing in sea port, are identified, and the elaborated model for assessing risk level with the use of assumptions of fuzzy logic theory, is presented. Also, a simulation of servicing reefer containers in port, was performed. Moreover a prototype of an expert system which makes it possible to take correct decisions on servicing reefer containers in sea port, depending on impact level of risk factors, was proposed

Six Sigma Approach for the Straddle Carrier Routing Problem

This paper discusses how to route straddle carriers in port container terminals. This problem is solved in the context of optimizing transport operations. The contribution of the work lies in the formulation and subsequent development of a Six Sigma Approach solution for the problem. Generating and prioritizing the critical Six Sigma transportation plans, however, are real challenges in practice. This study aims to develop a novel approach based on a combined ANP and DEMATEL technique to help container terminals determine critical Six Sigma transportation plans. An empirical case study is used to explore the effectiveness of the proposed approach.

The imperative for commodity-based intermodal freight transport demand modelling: a South African case study

Container forecasting typically focuses on its intermodal nature, container sizes and port container terminals. This leads to a commodity-blind approach to container forecasting, where the twenty-foot-equivalent is the forecasting output. The standardized unit is also increasing into many non-standard forms, indicated by the three main container market segments. This research deconstructs these segments and provides methodological and actual commodity-based container forecasting results for South Africa where intermodal solutions are still in its infancy and investments need to be made based on accurate forecasting

Transshipment Modeling and Simulation of Container Port Terminals

The growth of containerization and transporting goods in containers has generated capacity and equipment allocation problems in maritime ports. Container terminals represent complex systems with dynamic interactions between the various handling, transportation and storage units, and uncertainties about future events. Maritime container terminal operates at full capacity if the arrival of vessels to berth is uniform according to its capacity and equipment operating at constant parameters. Since there are random factors both on the arrival of ships and on the operation of equipments, the paper analyzes the influence of these factors on the terminal capacity. Therefore, we proposed a generic simulation model structure for the comparative assessment of the measures of performance of maritime terminal in ideal conditions (without perturbations in the terminal operation) and in different statistical assumptions of vessels inflows to berth and number of containers to unload per vessel. Based on event driven and virtual reality technology, the handling technology simulation model is developed using ARENA simulation software. The model is set-up by combining three basic functions: transport, transfer, and stacking. The transport activity is assumed by the flows of the container vessels and trucks. Different characteristics of the arrival flows are assumed (intervals between transport units, number of containers to unload). Quay cranes provide the container transfer. The stacking areas consist in one capacity area on the quay for the quick transfer on trucks. The simulation results lead to the conclusion that it can be achieved berth high occupancy and minimization of vessels waiting time at the port if the vessels inflows follow a distribution with small variance around the ideal value.

Heuristic Algorithms for Constructing Transporter Pools in Container Terminals

In port container terminals, containers are transported between vessels and storage blocks by transporters. To improve the utilization of transporters and the operational efficiency of container terminals, the pooling strategy is widely applied, and transporters in the same pool are shared by a group of quay cranes (QCs). This paper compares various strategies for constructing the pools: one pool for each QC, one pool for all the QCs deployed to each vessel, one pool for all the QCs for multiple adjacent vessels, and one pool for all the operating QCs in the terminal. Various heuristic algorithms (HAs) to construct pools of transporters are suggested and evaluated in terms of the total delay time of QC operation and the total travel distance of transporters. In addition, opportunities for dual-command-cycle operation are analyzed for each of these heuristic rules by using different data sets of QC operations. Various scenarios of QC operation are generated, and the HAs are compared in terms of their performance through a simulation study.