Models and algorithms for berth allocation problems in port terminals

Seaports play a key role in maritime commerce and the global market economy. Goods of different kinds are carried in specialized vessels whose handling requires ad hoc port facilities. Port terminals comprise the quays, infrastructures, and services dedicated to handling the inbound and outbound cargo carried on vessels. Increasing seaborne trade and ever-greater competition between port terminals to attract more traffic have prompted new studies aimed at improving their quality of service while reducing costs. Most terminals implement operational planning to achieve more efficient usage of resources, and this poses new combinatorial optimization problems which have attracted increasing attention from the Operations Research community. One of the most important problems confronted at the quayside is the efficient allocation of quay space to the vessels calling at the terminal over time, also known as the Berth Allocation Problem. A closely related problem arising in terminals that specialize in container handling concerns the efficient assignment of quay cranes to vessels, which, together with quay space planning, leads to the Berth Allocation and Quay Crane Assignment Problem. These problems are known to be especially hard to solve, and therefore require designing methods capable of attaining good solutions in reasonable computation times. This thesis studies different variants of these problems considering well-known and new real-world aspects, such as terminals with multiple quays or irregular layouts. Mathematical programming and metaheuristics techniques are extensively used to devise tailored solution methods. In particular, new integer linear models and heuristic algorithms are developed to deal with problem instances of a broad range of sizes representing real situations. These methods are evaluated and compared with other state-of-the-art proposals through various computational experiments on different benchmark sets of instances. The results obtained show that the integer models proposed lead to optimal solutions on small instances in short computation times, while the heuristic algorithms obtain good solutions to both small and large instances. Therefore, this study proves to be an effective contribution to the efforts aimed at improving port efficiency and provides useful insights to better tackle similar combinatorial optimization problems

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

Port Terminal Appointment Scheduling Problem

El constante aumento del transporte marítimo de los últimos años ha llevado a los operadores de terminales marítimas a investigar nuevas soluciones que aumenten su rendimiento. Un ejemplo actual es la resolución publicada por la Agencia del Petróleo de Brasil en julio de 2022, en la que destaca la importancia de contar con una metodología de programación de citas estructurada para organizar las operaciones buque-tierra.Esta investigación tiene tres objetivos principales: el primero de ellos es abordar el problema de programar citas desde diferentes perspectivas para ayudar al proceso de diseño de tales soluciones. El segundo es facilitar modelos de programación de citas que puedan ayudar a las terminales en sus procesos de optimización. El tercero es estudiar diferentes planteamientos sobre el valor de la información, diferentes plazos de programación, coordinación entre los equipos operativos y de programación, diferentes perfiles de congestión de la agenda, niveles de incertidumbre y normas de programación de atraque, entre otros.El reto consiste en encontrar un plan de cita optimizado que permita maximizar las ganancias de las terminales, considerando particularidades de cada solicitud de operación, incertidumbres en plazos de llegada y en procesamiento de los buques, los costes y ganancias vinculados a los contratos y la norma de secuenciación de atraques que utilizan los equipos operativos.Por un lado, existirán contribuciones en la parte de gestión a través de ideas que pueden impulsar el rendimiento de las terminales. Por otro lado, existirán aportaciones académicas a través de propuestas de modelos de programación de citas que incorporan la aleatoriedad en parámetros y consideran las llegadas como variables endógenas, conforme a diferentes perfiles de solapamiento de la agenda. Por tanto, se propondrán varias heurísticas, que abordarán los problemas de programación de citas aleatorios, enteros y no lineales (SINP, por sus siglas en inglés). Tienen en cuenta las solicitudes de los clientes, los acuerdos contractuales, las distribuciones de plazos de retraso / procesamiento y la norma predefinida de secuencia de atraques como insumos. En función de lo rentable que sean las operaciones, se define qué buques se aceptan o rechazan para operar, así como la fecha de la cita que se espera que se produzca.Debido a cuestiones de dimensionalidad, se propone una metodología de descomposición llamada ¿Cluster First, Schedule Second¿ (Primero agrupar, luego programar) con el fin de reducir el plazo de resolución. El problema principal se descompone en otros más pequeños que se resuelven de manera secuencial mediante la aproximación de la media muestral, de manera que la programación de cada grupo afecta a los siguientes. Los resultados de los modelos de optimización también se evalúan en un entorno de simulación de acontecimientos discreto que reproduce varias restricciones presentes en terminales congestionadas.Por último, se propondrá un conjunto de diez preguntas de investigación que guiarán todo el proceso de experimentación utilizado para probar diferentes temas sobre el problema de programación de citas de terminales portuarias. Entre las conclusiones, cabe destacar que los resultados muestran que las terminales especialmente congestionadas pueden lograr mejoras significativas en beneficios con medidas como las que se presentarán. También, se puede estudiar dar incentivos a los clientes para obtener más información por adelantado sobre la operación, así como aumentar la flexibilidad en la disponibilidad de días. Responder a los clientes de forma estadística dio mejores resultados, puesto que la terminal puede tomar la decisión con toda la información. En caso de que los clientes valoren respuestas dinámicas, una sugerencia podría ser ofrecerles un servicio superior para reducir el impacto general. En términos de normas de atraque, el método FIFO presentó buenos resultados en el caso de terminales con agendas congestionadas, mientras que la norma por programación fue mejor en situaciones con poco solapamiento. En el caso de llegadas al mismo tiempo, se recomienda priorizar en función de las desviaciones más pequeñas. Además, un resultado sorprendente es que las incertidumbres en las llegadas pueden, en algunos casos, ser beneficiosas, pero aceptar ventanas de tiempo en lugar de una fecha programada no lo es.<br /

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

Genetic algorithm for integrated model of berth allocation problem and quay crane scheduling with noncrossing safety and distance constraint

Berth Allocation and Quay Crane Scheduling are the most important part of container terminal operations since berth and quay cranes are an interface of ocean-side and landside in any port container terminal operation. Their operations significantly influence the efficiency of port container terminals and need to be solved simultaneously. Based on the situation, this study focuses on an integrated model of Continuous Berth Allocation Problem and Quay Crane Scheduling Problem. A comprehensive analysis of safety distance for vessel and non-crossing constraint for quay crane is provided. There are two integrated model involved. For the first integrated model, non-crossing constraints are added wherein quay cranes cannot cross over each other since they are on the same track. The second integrated model is focused on the safety distance between vessels while berthing at the terminal and at the same time, quay crane remains not to cross each other. These two constraints were selected to ensure a realistic model based on the real situation at the port. The objective of this model is to minimise the processing time of vessels. A vessel's processing time is measured between arrival and departure including the waiting time to be berthed and servicing time. A new algorithm is developed to obtain the good solution. Genetic Algorithm is chosen as a method based on flexibility and can apply to any problems. There are three layers of algorithm that provide a wider search to the solution space for vessel list, berth list, and hold list developed in this study. The new Genetic Algorithm produced a better solution than the previous research, where the objective function decreases 5 to 12 percent. Numerical experiments were conducted and the results show that both integrated models are able to minimize the processing time of vessels and can solve problem quickly even involving a large number of vessels. Studies have found that the safety distance set as 5 percent of vessel length gives the best solution. By adding safety distance to the integrated model with non-crossing constraint, the result indicates no improvement in the model objective function due to increasing distance between vessels. The objective function increases in the range of 0.4 to 8.6 percent. However, the safety distance constraint is important for safety and realistic model based on the port’s real situation

The technical efficiency of SACU Ports: a data envelopment analysis approach

There ever growing international trade and increasing congestion of ports led to an increased focus attention on technical efficiency. Seaports are a central and necessary component in facilitating international trade. Yet, there is only limited comprehensive information available on the technical efficiency of African ports. The study investigated the technical efficiency of the SACU ports during the period 2014-2019 using DEA model. The DEA model is effective in resolving the measurement of port efficiency since the calculations are nonparametric and do not need definition or knowledge of a priori weights for the inputs or outputs, as is necessary for estimate of efficiency using production functions. To identify the roots of the technical inefficiency of the SACU ports, the study subdivided technical efficiency into pure technical and scale efficiency. The model used cargo handled, container throughput, ship calls as output variables. Whilst, quay cranes, number of tugboats, draft, quay length and number of quays were used as input variables. The study used the scores of DEA-BCC model as explanatory variables in Tobit model. The results showed that quay cranes and quay length are the cause of technical inefficiencies in the ports.Thesis (MCom (Economics)) -- Faculty of Business and Economic Sciences, 202

The technical efficiency of SACU Ports: a data envelopment analysis approach

There ever growing international trade and increasing congestion of ports led to an increased focus attention on technical efficiency. Seaports are a central and necessary component in facilitating international trade. Yet, there is only limited comprehensive information available on the technical efficiency of African ports. The study investigated the technical efficiency of the SACU ports during the period 2014-2019 using DEA model. The DEA model is effective in resolving the measurement of port efficiency since the calculations are nonparametric and do not need definition or knowledge of a priori weights for the inputs or outputs, as is necessary for estimate of efficiency using production functions. To identify the roots of the technical inefficiency of the SACU ports, the study subdivided technical efficiency into pure technical and scale efficiency. The model used cargo handled, container throughput, ship calls as output variables. Whilst, quay cranes, number of tugboats, draft, quay length and number of quays were used as input variables. The study used the scores of DEA-BCC model as explanatory variables in Tobit model. The results showed that quay cranes and quay length are the cause of technical inefficiencies in the ports.Thesis (MCom (Economics)) -- Faculty of Business and Economic Sciences, 202

The Operational Planning Model of Transhipment Processes in the Port

Modelling of a traffic system refers to the efficiency of operations for establishing successful business performance by examining the possibilities for its improvement. The main purpose of each container terminal is to ensure continuity and dynamics of the flow of containers. The objective of this paper is to present a method for determining the amount of certain types of containers that can be transhipped at each berth, with the proper cargo handling, taking into account minimum total costs of transhipment. The mathematical model of planning the transhipment and transportation of containers at the terminal is presented. The optimal solution, obtained with the method of linear programming, represents a plan for container deployment that will ensure effective ongoing process of transhipment, providing the lowest transhipment costs. The proposed model, tested in the port of Rijeka, should be the basis for makingadequate business decisions in the operational planning of the container terminal.</p

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