Sea Container Terminals

Due to a rapid growth in world trade and a huge increase in containerized goods, sea container terminals play a vital role in globe-spanning supply chains. Container terminals should be able to handle large ships, with large call sizes within the shortest time possible, and at competitive rates. In response, terminal operators, shipping liners, and port authorities are investing in new technologies to improve container handling infrastructure and operational efficiency. Container terminals face challenging research problems which have received much attention from the academic community. The focus of this paper is to highlight the recent developments in the container terminals, which can be categorized into three areas: (1) innovative container terminal technologies, (2) new OR directions and models for existing research areas, and (3) emerging areas in container terminal research. By choosing this focus, we complement existing reviews on container terminal operations

Analysis and Optimization of Chassis Movements in Transportation Networks with Centralized Chassis Processing Facilities

This work studies the concept of “Centralized Processing of Chassis,” and its potential impact on port drayage efficiency. The concept revolves around an off-dock terminal (or several off-dock terminals), referred to as Chassis Processing Facilities (CPFs). A CPF is located close to the port, where trucks will go to exchange chassis, thereby reducing traffic at the marine terminals and resulting in reduced travel times and reduced congestion. This work is divided into two major studies: one at the strategic planning level, and one at the operational level for individual trucking companies. In the first study, an analytical framework for modeling and optimization of chassis movements in transportation networks with CPFs is developed, and a case study in the Long Beach/Los Angeles (LB/LA) port area is performed. Comparisons between current practices at ports, in which chassis exchanges occur at marine terminals, and proposed practices, in which the exchanges happen at CPFs, are performed. The results of this study indicate that a reduction of total travel time by up to 20% can be achieved when using the CPFs. The study also shows that, in the LB/LA port area, the return on investment for establishing additional CPF locations decreases sharply for any more than three CPFs. Overall, the findings indicate that travel time can be significantly reduced through implementation of CPFs which has important implications in reducing negative environmental impacts of the port as well as operational costs for trucking companies. In the second study, scheduling of chassis and container movements is optimized at the operational level for individual trucking companies, when CPFs are available for use within a major metropolitan area. A multi-objective optimization problem is formulated in which the weighted combination of the total travel time for the schedules of all vehicles in the company fleet and the maximum work span across all vehicle drivers during the day is minimized. Time-varying dynamic models for the movements of chassis and containers are developed and used in the optimization process. The optimal solution is obtained through a genetic algorithm, and the effectiveness of the developed methodology is evaluated through a case study which once again focuses on the LB/LA port area. The case study uses a trucking company located in the Los Angeles region, which can utilize three candidate CPFs for exchange of chassis. The company assigns container movement tasks to its fleet of trucks, with warehouse locations spread across the region. In the simulation scenarios developed for the case study, the use of CPFs at the trucking company level, can provide improvements up to 30% (depending upon the specific scenario) over the cases not using any CPFs. It is found in this work that for typical cases where the number of jobs is much larger than the number of vehicles in the company fleet, the greatest benefit from CPF use would be in the cases where there are some significant job-to-job differences with respect to chassis usage and type. Lastly, in addition to the formulation and optimization for initially planning daily activities, the study further models the problem in a dynamic environment, in which traffic network parameters can change drastically from initial daily predictions. In order to perform the optimization in a dynamic formulation with varying noise levels, a method by which noise could be injected into the initial daily predictions is developed to support the model inputs for the case study and an incremental optimization approach is implemented. Results indicate that a modest potential benefit of approximately 2% may be expected if dynamic re-routing is performed. However, in practice it will be important to weigh the cost of the additional real-time queries required to enable the dynamic re-routing against the potential benefits for the specific company and job set in question prior to implementation

Agent-based Truck Appointment System for Containers Pick-up Time Negotiation

Congestion in the seaports area is a common issue in many parts of the world. Fluctuating truck arrival has been identified as one of the significant determinants of congestion. In response, a truck appointment system (TAS) is introduced to manage truck arrival, particularly at peak times. In the existing TAS mechanism, the scheduling decision is centralized and disregards the concerns of trucking companies. Moreover, TAS may complicate the business operation of trucking companies that already have a constrained truck schedule. This study proposes a decentralized negotiation mechanism in TAS that allows trucking companies to adjust arrival times by utilizing the waiting time estimation provided by the terminal operator. We develop an agent-based model of a TAS in the container terminal pick-up procedure. The simulation results indicate that compared to the existing TAS mechanism, the negotiation TAS mechanism generates a shorter average truck turnaround time regardless of truck arrival rates. In terms of average net time cost, the negotiation TAS mechanism provides better value under high truck arrival rate conditions. The incentive for trucking companies to participate in the negotiations is even higher at peak times

Sequence-Based Simulation-Optimization Framework With Application to Port Operations at Multimodal Container Terminals

It is evident in previous works that operations research and mathematical algorithms can provide optimal or near-optimal solutions, whereas simulation models can aid in predicting and studying the behavior of systems over time and monitor performance under stochastic and uncertain circumstances. Given the intensive computational effort that simulation optimization methods impose, especially for large and complex systems like container terminals, a favorable approach is to reduce the search space to decrease the amount of computation. A maritime port can consist of multiple terminals with specific functionalities and specialized equipment. A container terminal is one of several facilities in a port that involves numerous resources and entities. It is also where containers are stored and transported, making the container terminal a complex system. Problems such as berth allocation, quay and yard crane scheduling and assignment, storage yard layout configuration, container re-handling, customs and security, and risk analysis become particularly challenging. Discrete-event simulation (DES) models are typically developed for complex and stochastic systems such as container terminals to study their behavior under different scenarios and circumstances. Simulation-optimization methods have emerged as an approach to find optimal values for input variables that maximize certain output metric(s) of the simulation. Various traditional and nontraditional approaches of simulation-optimization continue to be used to aid in decision making. In this dissertation, a novel framework for simulation-optimization is developed, implemented, and validated to study the influence of using a sequence (ordering) of decision variables (resource levels) for simulation-based optimization in resource allocation problems. This approach aims to reduce the computational effort of optimizing large simulations by breaking the simulation-optimization problem into stages. Since container terminals are complex stochastic systems consisting of different areas with detailed and critical functions that may affect the output, a platform that accurately simulates such a system can be of significant analytical benefit. To implement and validate the developed framework, a large-scale complex container terminal discrete-event simulation model was developed and validated based on a real system and then used as a testing platform for various hypothesized algorithms studied in this work

Models and Solutions Algorithms for Improving Operations in Marine Transportation

International seaborne trade rose significantly during the past decades. This created the need to improve efficiency of liner shipping services and marine container terminal operations to meet the growing demand. The objective of this dissertation is to develop simulation and mathematical models that may enhance operations of liner shipping services and marine container terminals, taking into account the main goals of liner shipping companies (e.g., reduce fuel consumption and vessel emissions, ensure on-time arrival to each port of call, provide vessel scheduling strategies that capture sailing time variability, consider variable port handling times, increase profit, etc.) and terminal operators (e.g., decrease turnaround time of vessels, improve terminal productivity without significant capital investments, reduce possible vessel delays and associated penalties, ensure fast recovery in case of natural and man-made disasters, make the terminal competitive, maximize revenues, etc.). This dissertation proposes and models two alternatives for improving operations of marine container terminals: 1) a floaterm concept and 2) a new contractual agreement between terminal operators. The main difference between floaterm and conventional marine container terminals is that in the former case some of import and/or transshipment containers are handled by off-shore quay cranes and placed on container barges, which are further towed by push boats to assigned feeder vessels or floating yard. According to the new collaborative agreement, a dedicated marine container terminal operator can divert some of its vessels for the service at a multi-user terminal during specific time windows. Another part of dissertation focuses on enhancing operations of liner shipping services by introducing the following: 1) a new collaborative agreement between a liner shipping company and terminal operators and 2) a new framework for modeling uncertainty in liner shipping. A new collaborative mechanism assumes that each terminal operator is able to offer a set of handling rates to a liner shipping company, which may result in a substantial total route service cost reduction. The suggested framework for modeling uncertainty is expected to assist liner shipping companies in designing robust vessel schedules

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