Integrated Scheduling of Vessels, Cranes and Trains to Minimize Delays in a Seaport Container Terminal

The multiple processes taking place on a daily basis at an intermodal container terminal are often considered individually, given the complexity of their joint consideration. Nevertheless, the integrated planning and scheduling of operations in an intermodal terminal, including the arrivals and departures of trains and vessels, is a very relevant topic for terminal managers, which can benefit from the application of Operations Research (OR) techniques to obtain near-optimal solutions without excessive computational cost. Applying the functional integration technique, we present here a mathematical model for this terminal planning process, and solve it using heuristic procedures, given its complexity and size. Details on the benchmark comparison of a genetic algorithm, a simulated annealing routine and a tabu search are provided for different problem instances

Simultaneous allocation and scheduling of quay cranes, yard cranes, and trucks in dynamical integrated container terminal operations

We present a dynamical modeling of integrated (end-to-end) container terminal operations using finite state machine (FSM) framework where each state machine is represented by a discrete-event system (DES) formulation. The hybrid model incorporates the operations of quay cranes (QC), internal trucks (IT), and yard cranes (YC) and also the selection of storage positions in container yard (CY) and vessel bays. The QC and YC are connected by the IT in our models. As opposed to the commonly adapted modeling in container terminal operations, in which the entire information/inputs to the systems are known for a defined planning horizon, in this research we use real-time trucks, crane, and container storage operations information, which are always updated as the time evolves. The dynamical model shows that the predicted state variables closely follow the actual field data from a container terminal in Tanjung Priuk, Jakarta, Indonesia. Subsequently, using the integrated container terminal hybrid model, we proposed a model predictive algorithm (MPA) to obtain the near-optimal solution of the integrated terminal operations problem, namely the simultaneous allocation and scheduling of QC, IT, and YC, as well as selecting the storage location for the inbound and outbound containers in the CY and vessel. The numerical experiment based on the extensive Monte Carlo simulation and real dataset show that the MPA outperforms by 3-6% both of the policies currently implemented by the terminal operator and the state-of-the-art method from the current literature

Discrete-Event Control and Optimization of Container Terminal Operations

This thesis discusses the dynamical modeling of complex container terminal operations. In the current literature, the systems are usually modeled in static way using linear programming techniques. This setting does not completely capture the dynamic aspects in the operations, where information about external factors such as ships and trucks arrivals or departures and also the availability of terminal's equipment can always change. We propose dynamical modeling of container terminal operations using discrete-event systems (DES) modeling framework. The basic framework in this thesis is the DES modeling for berth and quay crane allocation problem (BCAP) where the systems are not only dynamic, but also asynchronous. We propose a novel berth and QC allocation method, namely the model predictive allocation (MPA) which is based on model predictive control principle and rolling horizon implementation. The DES models with asynchronous event transition is mathematically analyzed to show the efficacy of our method. We study an optimal input allocation problem for a class of discrete-event systems with dynamic input sequence (DESDIS). We show that in particular, the control input can be obtained by the minimization/maximization of the present input sequence only. We have shown that the proposed approach performed better than the existing method used in the studied terminal and state-of-the-art methods in the literature

Subsampling OFDM-based ultrasonic data communication through metallic channels for monitoring of cargo containers

An enhanced ultrasonic communication system based on piezoelectric transducers for monitoring of goods in cargo containers is presented. The proposed system consists of several sensors placed inside the container, whose data are collected and transmitted outside it. Data transmission is carried out by an ultrasonic communication channel, in order to avoid drilling the wall of the container. The proposed data communication system is based on the transmission of a 128-OFDM signal. This modulation has been chosen due to its robustness to channels with frequency-selective fading and its spectrum efficiency. In order to increase the signal bandwidth and to reduce the power consumption at the internal node (transmitter), the proposed system exploits the non-linearity of the metallic channel to transmit at higher resonance frequencies. Moreover, power consumption at the external node (receiver) is reduced by using a subsampling based receiver, which allows its implementation by low-cost electronics.This work was supported by the Spanish Ministry of Economy and Competitiveness under Projects TEC2016-80396-C2-2-R and TEC2016-80396-C2-1-

The synergistic effect of operational research and big data analytics in greening container terminal operations: a review and future directions

Container Terminals (CTs) are continuously presented with highly interrelated, complex, and uncertain planning tasks. The ever-increasing intensity of operations at CTs in recent years has also resulted in increasing environmental concerns, and they are experiencing an unprecedented pressure to lower their emissions. Operational Research (OR), as a key player in the optimisation of the complex decision problems that arise from the quay and land side operations at CTs, has been therefore presented with new challenges and opportunities to incorporate environmental considerations into decision making and better utilise the ‘big data’ that is continuously generated from the never-stopping operations at CTs. The state-of-the-art literature on OR's incorporation of environmental considerations and its interplay with Big Data Analytics (BDA) is, however, still very much underdeveloped, fragmented, and divergent, and a guiding framework is completely missing. This paper presents a review of the most relevant developments in the field and sheds light on promising research opportunities for the better exploitation of the synergistic effect of the two disciplines in addressing CT operational problems, while incorporating uncertainty and environmental concerns efficiently. The paper finds that while OR has thus far contributed to improving the environmental performance of CTs (rather implicitly), this can be much further stepped up with more explicit incorporation of environmental considerations and better exploitation of BDA predictive modelling capabilities. New interdisciplinary research at the intersection of conventional CT optimisation problems, energy management and sizing, and net-zero technology and energy vectors adoption is also presented as a prominent line of future research

The synergistic effect of operational research and big data analytics in greening container terminal operations: A review and future directions

Container Terminals (CTs) are continuously presented with highly interrelated, complex, and uncertain planning tasks. The ever-increasing intensity of operations at CTs in recent years has also resulted in increasing environmental concerns, and they are experiencing an unprecedented pressure to lower their emissions. Operational Research (OR), as a key player in the optimisation of the complex decision problems that arise from the quay and land side operations at CTs, has been therefore presented with new challenges and opportunities to incorporate environmental considerations into decision making and better utilise the ‘big data’ that is continuously generated from the never-stopping operations at CTs. The state-of-the-art literature on OR's incorporation of environmental considerations and its interplay with Big Data Analytics (BDA) is, however, still very much underdeveloped, fragmented, and divergent, and a guiding framework is completely missing. This paper presents a review of the most relevant developments in the field and sheds light on promising research opportunities for the better exploitation of the synergistic effect of the two disciplines in addressing CT operational problems, while incorporating uncertainty and environmental concerns efficiently. The paper finds that while OR has thus far contributed to improving the environmental performance of CTs (rather implicitly), this can be much further stepped up with more explicit incorporation of environmental considerations and better exploitation of BDA predictive modelling capabilities. New interdisciplinary research at the intersection of conventional CT optimisation problems, energy management and sizing, and net-zero technology and energy vectors adoption is also presented as a prominent line of future research

Tidal vessels constrained in movement in the port of Durban: associated cargo costs and potential remedies.

Masters Degree. University of KwaZulu-Natal, Durban.Large container callers into the port of Durban are not able to explore their inherent captive capacities, resulting in restricted cargo flow through the country aligned to the permissible draft, thus having an adverse impact on seaborne commerce and the wider economy of the country. It is therefore crucial for the berth deepening project to take its intended shape as deeper berths will facilitate the modern generation of large container vessels to be exploited to its full loadable capacity at the summer marks. This will enhance a secure and improved complementarity within the South African ports system, in respect of their roles as both gateway and trans-shipment hub ports for containers. The direct and indirect losses to Transnet and the shipping lines due to the methodical and phased erosion of trans-shipment volumes have been elucidated. The main contributory factors to the loss in trans-shipment volumes have been attributed to capacity constraints stemming out of draft limitations at Durban, as well as the vital component of port operations, namely, efficiency. In the interim, in order to mitigate the constraints, as a short-term remedy for partial recovery with regards to optimisation in cargo liftings, it has been proposed that Durban adopts the concept of operating as a NAABSA port, whereby working container vessels that are “Not Always Afloat But Safely Aground” may sustain continuous working operations while alongside at the port’s container berths, in place of the current stop-start operations. Both the vessels and the port are shown to possess all the essential credentials to safely execute this widely practised manoeuvre. To this effect, the structural integrity of the container ships has been established beyond any reservation, for the fitness of the NAABSA operation while working cargo, as has the plane and homogeneous nature of the seabed in the port of Durban. Regional competitor ports in the southern African region, in their drive to attract additional container volumes through their terminals, are creating capacity ahead of demand, to a point where they may be perceived as a threat to the dominance of the port of Durban. The status quo of these regional foreign ports gives an insight to the infrastructural developments and equipment status. This could perhaps instil a sense of circumspection for Transnet to forge ahead in the right direction.Author name captured as Ian Santana Martin Rosario in PDF

Application of Mixed Simulation Method to Modelling Port Traffic

Marine ports are the largest single business complex in the maritime sector impacting the coastal, marine, and atmospheric environment. The environmental effects of port operations mostly originate from the vessel and cargo handling operations, and maintenance. Port operations generate marine pollution in many forms (chemical, biological, solid waste, and sedimentation) and present a challenge to all port operators. Because ports are often located near urban areas, the wider impact of port operations on the environment cannot be ignored as it can potentially affect the economy of these areas as a whole. Air pollution is a significant externality for ports located close to urban areas. Around 4.5% and 6.2% of the total SO2 and NOX respectively, emitted by ships are due to in-port activities such as manoeuvring (approaching harbours) and hoteling (at the dock in port). A vessel consumes around 10% of fuel during slow manoeuvring. Assuming around 4.5% and 6.2% of the total SO2 and NOx emitted by ships are due to in-port activities such as manoeuvring (approaching harbours) and hoteling (at the dock in port), simplifying the traffic model hinders the ability to conduct accurate emission assessment and limits the ability to conduct an environmental assessment as a result of increased port capacity. The research aim is to develop a multi-method simulation model of port systems to simulate port traffic for assessing various port challenges like emission, throughputs, etc. The study will develop a mixed simulation model of port systems comprising of marine traffic and associated processes using the port of Liverpool as a case study. The developed simulation model will be used to estimate emission within the case study port. The study developed a multi-method simulation model representing individual actors and specific processes of the entire port system. The developed simulation method integrates two major modelling approaches: discrete-event simulation and agent-based simulation. Due to the complexity within the port, the study focused on the vessel and cargo handling sector of the port because manoeuvring (approaching harbours) is a significant source of pollution. The developed method adopts an object-oriented approach. Object-oriented modelling is an important aspect of the modelling methodology because it supports the reusability and scalability of the developed model as entities are represented as objects with specific characteristics based on their types. This is significant in representing vessel and cargo terminal types. Each vessel type was encapsulated with internal characteristics e.g. passage plan, speed, etc. A terminal developed to handle bulk cargoes is different from a terminal that handles container cargoes. Therefore, agents were developed to represent various cargo terminal types (such as container terminal, bulk terminal, passenger terminal, etc.), with each terminal type possessing its characteristics specific to itself. The method was applied in the study area. AIS data was collected for the Port of Liverpool over the 12 months of 2016. The data provides information on all marine traffic (fitted with AIS) for the Port of Liverpool outer channel (Liverpool Bay) and the port inbound and outbound lanes along the River Mersey. This data set was used to design and validated the simulation model. A maximum of seven vessels was observed to be transiting through the outer waterway, four at the inner and two in the manoeuvring waterway. Vessel transit times and speed variation are observed to be influenced by the vessel traffic density within each waterway. Vessel waiting and dwell time are seen to be influenced by lock availability and the tidal condition of the port. An increase in tidal duration results in an increase in both waiting and dwell time and vice versa. The validation outcome reveals that the developed model also possesses a relative realistic speed changing behaviour when compared to real-world data. The simulation result also shows a realistic relationship with the travel time distribution from the historical data set. The developed model represents the port as an entire system, however, the study only focussed on the vessel handling process. Previous port modelling has witnessed lots of simplification in vessel traffic models, port process models, and exclusions of external condition models over the years, but the object-oriented programme implemented in this study can help solve these issues. Therefore, the developed methodology would enable better models to be integrated