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

Modelling the performance of port terminals using microsimulation

[EN] Globalization has caused an increase in cargo volumes in ports, which is starting to produce congestion in some of the main ports, delays in the whole supply chain, higher costs, retention in the vicinity of ports, and more pollution. All of these issues highlight the need to improve current container terminals by searching for enhanced management models. The terminal operating system (TOS) is the operational control system used in container terminals. An improvement of TOS with better functionalities, and their optimization, would increase the efficiency of the terminal. In a previous study, the authors identified and weighted TOS functionalities using the analytic hierarchy process (AHP) method. The aim of this paper is to analyse by simulation how the improvement of the most influential TOS functionalities affects the operational and the environmental performance of a container terminal. Two new TOSs (TOS 2 and TOS 3) were compared with the TOS (TOS 1) currently used at Intersagunto terminal (Spain) by microsimulation using FlexTerm. Results show that modifications to the TOS can improve certain operational aspects, such as the number of containers handled, the occupation of the storage yard, and the dwell times; however, there were not significant improvements in energy consumption and carbon footprint. Further developments should address this issue by modifying other TOS functionalities in order to obtain both operational and environmental improvements at the terminal. This paper is addressed to managers of container terminals, TOS designers, researchers in the field of ports and terminals, and port authorities.This study was co-funded by Instituto Valenciano de Competitividad (IVACE) and the European Regional Development Fund (ERDF) under project reference IMIDCA/2017/32.Hervás-Peralta, M.; Rozic, T.; Poveda-Reyes, S.; Santarremigia, FE.; Pastor-Ferrando, J.; Molero, GD. (2020). Modelling the performance of port terminals using microsimulation. European Transport / Trasporti Europei. (76):1-11. http://hdl.handle.net/10251/165840S1117

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

Optimization of yard operations in container terminals from an energy efficiency approach

This Thesis addresses common operational issues related to maritime container terminals. In the last decades, containerization of maritime transportation has grown very rapidly, forcing terminal operators to cope with unprecedented volumes of containers in a continuous manner. As a consequence, terminal efficiency is always a critical factor. In the near future, operators are also expected to face increasing operational costs deriving firstly from the energy crisis and secondly from new regulations enforcing ports to become more environmentally friendly. As a consequence, operational inefficiencies deriving from periods of congestion require innovative solutions and optimization techniques to improve the efficiency and productivity in the terminal yard. This Thesis addresses such problems by introducing an electric energy consumption model that characterizes energy expenditure of yard cranes. For each gantry, trolley and hoist movement of the cranes, the model takes into account the different resistances that must be overcome during the acceleration, constant speed and deceleration phases of each movement. The energy consumption model is coupled to two different discrete event simulation models of one parallel and one perpendicular container terminals, with the goal to analyze the handling operations and optimize energy efficiency and productivity. One additional innovative aspect of the works is that they include the effect of the volume of container traffic in the analysis with the aim to assess differences in the performance of the algorithms under a range of realistic scenarios, which is usually neglected in similar studies. Finally, in addition to stacking and retrieval operations, the works also introduce housekeeping operation, which are common in the real world but often disregarded in the literature. Such operations are relevant as they may be critical in terms of achieving good productivity, but on the other hand they amount for a significant portion of the overall energy consumption. In particular, the works of the Thesis deal have four particular objectives: (1) providing such flexible and customizable numerical models of discrete event type to simulate and analyze parallel and perpendicular terminals, (2) proposing a new stacking algorithm to reduce energy expenditure and improve automatic stacking crane productivity in perpendicular terminals; (3) optimizing the dimensions of a perpendicular layout; and (4) analyzing the distribution of containers in the yard layout as a function of the moment at which space for export containers is reserved while looking at the operational costs. In the first place, results show the models are capable of characterizing in detail the energy consumption associated to crane movements in both parallel and perpendicular terminals. With respect to perpendicular terminals, the proposed stacking algorithm is capable of improving the energy efficiency up to around 20% while achieving greater productivity at the same time. In addition, results show that the dimensions of a perpendicular terminal block can be optimized so as to improve the productivity; with respect to energy consumption, although a smaller block induces lesser electrical consumption, the random nature of housekeeping operations produce a significant degree of distortion in the results, revealing that such operations constitute a promising flied for future research. Finally, considering parallel terminals, a greater degree of clustering is observed as the reservation is made earlier. When considering the associated operational costs associated to yard cranes and yard trucks, greater clustering results in more efficient use of the energy, and therefore reservation may be desirable when possible to enhance terminal productivity.Esta Tesis aborda temas operativos comunes relacionados con terminales marítimas de contenedores. En las últimas décadas, la contenerización del transporte marítimo ha crecido exponencialmente, obligando a los operadores a hacer frente a volúmenes de contenedores sin precedentes de manera continuada. Como consecuencia, la eficiencia de las operaciones es siempre un factor crítico. En un futuro próximo, los operadores también deberán afrontar crecientes costes operativos derivados de la crisis energética, y también de nuevas regulaciones que obligan a los puertos a volverse más respetuosos con el medio ambiente. Por estos motivos, las ineficiencias operativas derivadas de períodos de congestión requieren soluciones innovadoras y técnicas de optimización para mejorar la eficiencia y productividad en los patios de contenedores. Esta tesis aborda estos problemas introduciendo un modelo de consumo de energía eléctrica que caracteriza el gasto de las grúas de patio. Para cada movimiento de "gantry", "hoist" y "spreader", el modelo tiene en cuenta las diferentes resistencias que deben superarse durante las fases de aceleración, velocidad constante y deceleración del movimiento. El modelo de consumo de energía se ha acoplado a dos modelos de simulación de eventos discretos de terminales de contenedores, una paralela y otra perpendicular, con el objetivo de analizar las operaciones de manipulación y optimizar la eficiencia energética y la productividad. Otro aspecto innovador de este trabajo es que analiza el efecto del volumen de tráfico de contenedores con el objetivo de evaluar el comportamiento de los algoritmos bajo un rango de escenarios realistas, lo que generalmente no se tiene en cuenta en estudios similares. Por último, además de las operaciones de apilamiento y salida de contenedores, la tesis también considera las operaciones de reordenamiento del patio, muy comunes en el mundo real, pero que a menudo no se tienen en cuenta en la literatura. Tales operaciones pueden ser críticas para lograr una buena productividad, pero por otra parte representan una parte importante del consumo total de energía. En particular, los trabajos desarrollados en esta Tesis tienen cuatro objetivos concretos: (1) proporcionar modelos numéricos flexibles y configurables de tipo eventos discretos para simular y analizar terminales paralelas y perpendiculares, (2) proponer un nuevo algoritmo de apilamiento para reducir el gasto de energía y mejorar la productividad de la grúa automático en terminales perpendiculares; (3) optimizar las dimensiones de un bloque de una terminal perpendicular; y (4) analizar la distribución de los contenedores en la disposición del patio en función del momento en que se reserva el espacio para los contenedores de exportación. Los resultados muestran que, en primer lugar, los modelos son capaces de caracterizar en detalle el consumo de energía asociado a los movimientos de las grúas en ambos tipos de terminales. Con respecto a las terminales perpendiculares, el algoritmo de apilado propuesto es capaz de mejorar la eficiencia energética hasta aproximadamente un 20%, al tiempo que se consigue una mayor productividad. Además, los resultados muestran que las dimensiones de un bloque perpendicular pueden optimizarse para mejorar la productividad; con respecto al consumo de energía, aunque un bloque más pequeño induce un menor consumo eléctrico, la naturaleza aleatoria de las operaciones de reordenación inducen un grado significativo de distorsión en los resultados, indicando que tales operaciones pueden ser objeto de futura investigación. Por último, respecto a las terminales paralelas, a medida que se adelanta la reserva de espacio los contenedores presentan un mayor grado de agrupación, lo que redunda en un uso más eficeficiente de la energía debido a los menores costos operacionales asociados a grúas y camiones de patio, por lo que la reserva puede ser aconsejable cuando sea posible para mejorar la productividad del termina

Automated Transfer Management Systems and the Intermodal Performance of North American Freight Distribution

For capacity, energy and environmental reasons, intermodal transportation is widely regarded as the preferable option for inland freight distribution. But because of the relatively high embedded costs, intermodal rail is currently only an attractive option for containerized goods carried over long distances. Transfers that in theory should entail only a few operations at a terminal in reality require multiple operations. This paper argues that by incorporating new terminal designs and an automated transfer management system (ATMS) at terminals and distribution centers, the resulting efficiency advances and productivity gains could significantly improve the economics for both long and short haul intermodal movements, including port shuttle trains. This system not only could significantly lower fixed costs and make intermodal more price competitive, but improve time and reliability to make intermodal more service competitive as well

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