Search results

This paper examines how the altering nature of planning decisions affects operational efficiency in seaport container terminals. The uncertainty and the role of the planner were investigated considering the dynamic integrated planning function of the quay to yard interface.

A system dynamics model has been built to illustrate the integrated dynamic environment. Data collection was conducted at a leading container terminal at a hub port. The model was simulated for different scenarios to derive findings.

The planner has been identified as the agent who makes alterations between the initial operational plan and the actual plan. The initial plan remains uncertain even when there is no impact from crane breakdowns, requiring a significant number of alterations to be made. The planner who had worked on the yard plan had altered (approximately 45%) the initial plan than the alterations done by the planner who had worked on the vessel plan. As a result, the feedback loop that is created by the remaining moves at each hourly operation influences the upcoming operation as much as crane breakdowns influence.

The uncertainty and the role of the planner were investigated considering the dynamic integrated planning function of the quay to yard interface. The findings of this study are significant since terminal efficiency is examined considering the quayside and landside as an integrated system.

This paper aims to forecast inbound and outbound container throughput for Bangkok Port to 2041 and uses the results to inform the future planning and management of the port’s container terminal.

The data used cover a period of 16 years (192 months of observations). Data sources include the Bank of Thailand and the Energy Policy and Planning Office. Cause-and-effect forecasting is adopted for predicting future container throughput by using a vector error correction model (VECM).

Forecasting future container throughput in Bangkok Port will benefit port planning. Various economic factors affect the volume of both inbound and outbound containers through the port. Three cases (scenarios) of container terminal expansion are analyzed and assessed, on the basis of which an optimal scenario is identified.

The economic characteristics of Thailand differ from those of other countries/jurisdictions, such as the USA, the EU, Japan, China, Malaysia and Indonesia, and optimal terminal expansion scenarios may therefore differ from that identified in this study. In addition, six particular countries/jurisdictions are the dominant trading partners of Thailand, but these main trading partners may change in the future.

There are only two major projects that have forecast container throughput volumes for Bangkok Port. The first project, by the Japan International Cooperation Agency, applied both the trend of cargo volumes and the relationship of volumes with economic indices such as population and gross domestic product. The second project, by the Port Authority of Thailand, applied a moving average method to forecast the number of containers. Other authors have used time-series forecasting. Here, the authors apply a VECM to forecast the future container throughput of Bangkok Port.

There is significant amount of literature tackling different issues related to the port industry. The present chapter focuses on a single business unit of seaports aiming at the documentation of works related to container terminals.

An effort to review, collect and present the majority of the works present in the last 30 years, between 1980 and 2010, has been made in order to picture the problems dealt and methods used by the authors in the specific research field. To facilitate the reader, studies have been grouped under five categories of addressed problems (productivity and competitiveness, yard and equipment utilization, equipment scheduling, berth planning, loading/unloading) and four modelling methodologies (mathematics and operations research, management and economics, simulation, stochastic modelling).

The analysis shows that most works focus on productivity and competitiveness issues followed by yard and equipment utilisation and equipment scheduling. In reference to the methodologies used managerial and economic approaches lead, followed by mathematics and operations research.

In reference to future research, two fields have been identified where there is scope of significant contribution by the academic community: container terminal security and container terminal supply chain integration.

The present chapter provides the framework for researchers in the field of port container terminals to picture the so far works in this research area and enables the identification of gaps at both research question and methodology level for further research.

This paper presents a generic simulation model to determine the equipment mix (quay, yard and intra-terminal transfer) for a Container Terminal Logistics Operations System (CTLOS). The simulation model for the CTLOS, a typical type of discrete event dynamic system (DEDS), consists of three sub-models: ship queue, loading-unloading operations and yard-gate operations. The simulation model is empirically applied to phase 1 of the Yangshan Deep Water Port in Shanghai. This study considers different scenarios in terms of container throughput levels, equipment utilization rates, and operational bottlenecks, and presents a sensitivity analysis to evaluate and choose reasonable equipment ratio ranges under different operational conditions.

The purpose of this paper is to investigate ways to reduce the average amount of exceeded guaranteed service time for external trucks at Deepwater Container Terminal Gdańsk Sp z o.o. (DCT Gdańsk) via dosing the gate activities, in particular IN-Gate entry process, of trucks carrying import/export/transit containers.

A Six Sigma methodology with the define, measure, analyze, improve, and Control (DMAIC) methods along with the SIPOC chart, cause and effect diagram, scatterplot, benchmark and brainstorming and finally multi-voting tool are used as analyses tools in this research.

DCT Gdańsk reorganized and modernized the gate operations. Gate reorganization and modernization include streaming line traffic at the gates, external parking lot optimization, implementation of dedicated supporting software and installation of dedicated CCTV cameras to provide 24 h live view. During gates development, the external truck service times data were collected and analysed. The obtained materials concerned the measurement of the average truck turnaround time before and after the implementation of the improvements.

The proposed approach of reducing the average amount of exceeded guaranteed service time of external trucks at the container terminal is unique and relatively cheap mainly due to organizational changes with some widely available low-cost investments and can be applied on a different scale to other container terminals or to transport and logistics companies.

The purpose of this study is to reveal the magnitude of empty container movements (ECM) arising from cargo seasonality by means of long-term datasets of Turkish terminals. Trade imbalance is one of the well-known major reasons of ECM. Cargo seasonality apart from some other operational drivers and market effect, i.e. commercial decisions of the ship operators, is the major operational driver in Turkish terminals effecting ECM. Furthermore, this study highlights the significance of market effect, leading to take measures for more effective empty container operations in terms of decision makers leading the ship operators.

Time series analysis of full container datasets was performed through X-13ARIMA-SEATS methodology, implementing seasonal adjustment.

The results indicate that 17 of 112 time series in hand, based on a terminal/hinterland, container type and “in and out” foreign trade, exhibit cargo seasonality. Roughly, the amount of ECM originating from cargo seasonality in Turkish terminals represents 10 per cent of total ECM except trade imbalance in those terminals where seasonality is present. This reveals that ECM arising from market effect should not be underestimated.

Reefer container traffic could not be sorted from the datasets.

This paper focuses on one of the major reasons of ECM, cargo seasonality. It brings a novel point of view and interpretations which were not suggested previously about ECM, motivating to overcome inefficiency in container operations.

When port authorities or terminal operators set the free time or increase storage density, the decision is often made without a clear understanding of their effects on throughput and rehandling productivity. This is partly because practical methods that deal specifically with the effect of dwell time on throughput and productivity are limited in the literature; hence the motivation for this work. This paper introduces simple methods to evaluate the effect of container dwell time and storage policies on import throughput, storage density, and rehandling productivity. The analysis considers two import storage strategies 1) non-mixed - no stacking of new import containers on top of old ones, and 2) mixed - stacking of new import containers on top of old ones. The results highlight the effect dwell time has on throughput and rehandling productivity. For the non-mixed storage policy, the increasing container dwell time lowers throughput and average stack height - resulting in an increase in rehandling productivity. On the other hand, for the mixed storage policy, the increasing container dwell time raises throughput and average stack height - resulting in a decrease in rehandling productivity. Using the presented methods, port authorities and terminal operators are able to assess and quantify the benefits of their decisions regarding container free time and subsequently make an informed decision.

The purpose of this paper is to study the impacts of time segment modeling approach for berth allocation and quay crane (QC) assignment on container terminal operations efficiency.

The authors model the small time segment modeling approach, based on minutes, which can be a minute, 15 min, etc. Moreover, the authors divided the problem into three sub-problems and proposed a novel three-level genetic algorithm (3LGA) with QC shifting heuristics to deal with the problem. The objective function here is to minimize the total service time by using different time segments for comparison and analysis.

First, the study shows that by reducing the time segment, the complexity of the problem increases dramatically. Traditional meta-heuristic, such as genetic algorithm, simulated annealing, etc., becomes not very promising. Second, the proposed 3LGA with QC shifting heuristics outperforms the traditional ones. In addition, by using a smaller time segment, the idling time of berth and QC can be reduced significantly. This greatly benefits the container terminal operations efficiency, and customer service level.

Nowadays, transshipment becomes the main business to many container terminals, especially in Southeast Asia (e.g. Hong Kong and Singapore). In these terminals, vessel arrivals are usually very frequent with small handling volume and very short staying time, e.g. 1.5 h. Therefore, a traditional hourly based modeling approach may cause significant berth and QC idling, and consequently cannot meet their practical needs. In this connection, a small time segment modeling approach is requested by industrial practitioners.

In the existing literature, berth allocation and QC assignment are usually in an hourly based approach. However, such modeling induces much idling time and consequently causes low utilization and poor service quality level. Therefore, a novel small time segment modeling approach is proposed with a novel optimization algorithm.

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.

The purpose of this paper is to propose a yard allocation model via objective programming. This is initially postulated based on a rolling‐horizon strategy, which aims at allotting outbound containers into yard.

To resolve the NP‐hard problem regarding the yard allocation model, a hybrid algorithm, which applies heuristic rules and distributed genetic algorithm (DGA), is then employed.

It could be observed from the case study that this proposed approach is proven effective for resolving the container yard allocation problem. The total loading time onto vessels, the total horizontal transportation distance and the imbalance among blocks are improved.

This paper does not deal with equipment scheduling.

This approach helps to minimize turnaround time; handling cost of vessels; the workloads among blocks are balanced for each vessel; and the total distance of container transportation.

This paper designs a hybrid algorithm, which integrates heuristic rules and DGA. In details, the heuristic rules are developed for generating feasible solutions, while the DGA was applied for optimizing these solutions.