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

Assessment of Quay and Yard Transshipment Operations Under Proximity Limitations in Multi-Terminal Container Ports

The assignment of storage locations and space has a considerable impact on the performance of container terminals. This holds especially in multi-terminal transshipment ports where the planning of inbound and outbound container flows needs to consider space limitations and travel distances for reallocations, causing both intra- and inter-terminal transports. Thus, in this work, we study the impact of closeness limitations on quay and yard areas when conducting transshipment operations at multi-terminal transshipment ports. In doing so, a mathematical formulation and several scenarios covering different distance policies for limiting the allocation of containers before vessel loading or unloading operations are assessed. At a tactical level, this paper provides insights on assignment decisions while assessing distance-based policies that can be incorporated in practice

Strategies for dynamic appointment making by container terminals

We consider a container terminal that has to make appointments with barges dynamically, in real-time, and partly automatic. The challenge for the terminal is to make appointments with only limited knowledge about future arriving barges, and in the view of uncertainty and disturbances, such as uncertain arrival and handling times, as well as cancellations and no-shows. We illustrate this problem using an innovative implementation project which is currently running in the Port of Rotterdam. This project aims to align barge rotations and terminal quay schedules by means of a multi-agent system. In this\ud paper, we take the perspective of a single terminal that will participate in this planning system, and focus on the decision making capabilities of its intelligent agent. We focus on the question how the terminal operator can optimize, on an operational level, the utilization of its quay resources, while making reliable appointments with barges, i.e., with a guaranteed departure time. We explore two approaches: (i) an analytical approach based on the value of having certain intervals within the schedule and (ii) an approach based on sources of exibility that are naturally available to the terminal. We use simulation to get insight in the benefits of these approaches. We conclude that a major increase in utilization degree could be achieved only by deploying the sources of exibility, without harming the waiting time of barges too much

Priority Control of Berth Allocation Problem in Container Terminals

This paper presents a decision support system for the core problem of berth allocation decision in a container terminal. The allocation of berths to the calling vessels is complex with the fact that different service level requirements are required for different vessels. Terminal managers demand for effective decision support systems that would aid them with the allocation problem considering service priorities. Consequently, this study provides a DSS, built by a dynamic discrete-event simulation model embedded with an optimization tool that determines the priority controls for the berth allocation to the calling vessels. To show the practical application of the DSS, a comprehensive case study from a Turkish container terminal considering the current state and future expansion plans that also provides an indication of the usability aspect of the program on other ports around the world has been conducted. Further experiments are conducted based on data from the Port of Rotterdam. The DSS presented in this study may help port authorities in determining more efficient allocation decisions within a container terminal

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

Optimization of operations in container terminals: hierarchical vs integrated approaches

Over the last years, international sea freight container transportation has grown dramatically and container terminals play nowadays a key role within the global shipping network. Terminal's operations have received increasing interest in the scientific literature and operations research techniques are more and more used to improve efficiency and productivity. In this work we provide an overview of container terminal's operations and associated decision problems. We review state-of-the-art optimization approaches in terminal's management and we discuss what are in our opinion the current research trends. In particular, we focus on the following streams: the integrated optimization of interdependent decision problems, the analysis of issues related to traffic congestion in the yard and the tactical planning of operations. The discussion is based on the Tactical Berth Allocation Problem (TBAP), an integrated decision problem that deals with the simultaneous optimization of berth allocation and quay crane assignment. Yard housekeeping costs are also taken into account in the objective function. We use the TBAP as a case study to illustrate the benefits of an integrated optimization approach. A comparative analysis with the traditional hierarchical solution approach is provided. Computational results based on real-world data provided by the MCT (port of Gioia Tauro, Italy) show that the additional computational effort required by the integrated optimization approach allows for more efficient solutions

Modeling and Solving the Tactical Berth Allocation Problem

In this paper we integrate at the tactical level two decision problems arising in container terminals: the berth allocation problem, which consists of assigning and scheduling incoming ships to berthing positions, and the quay crane assignment problem, which assigns to incoming ships a certain QC profile (i.e. number of quay cranes per working shift). We present two formulations: a mixed integer quadratic program and a linearization which reduces to a mixed integer linear program. The objective function aims, on the one hand, to maximize the total value of chosen QC profiles and, on the other hand, to minimize the housekeeping costs generated by transshipment flows between ships. To solve the problem we developed a heuristic algorithm which combines tabu search methods and mathematical programming techniques. Computational results on instances based on real data are presented and compared to those obtained through a commercial solver

The Tactical Berth Allocation Problem (TBAP) with quay crane assignment and transshipment-related quadratic yard costs

International sea-freight container transport has grown dramatically over the last years and container terminals play nowadays a key-role in the global shipping network. Increasing competition and competitiveness among terminals require more and more efficiency in container handling operations, both in the quayside and the landside, in order to better utilize limited resources (such as cranes, trucks, berths, storage space, etc.) as well as minimize ship's turnaround time. Operations research methods are therefore worth being use for the optimization of terminal operations. We take into account two decision problems which are usually solved hierarchically by terminal planners: the Berth Allocation Problem (BAP), which consists of assigning and scheduling incoming ships to berthing positions, and the Quay Crane Assignment Problem (QCAP), which assigns to incoming ships a certain QC profile (i.e. number of quay cranes per working shift). These two problems are indeed strictly correlated: the QC profile assigned to the incoming ships affects their handling time and has thus an impact on the berth allocation. In this work, we aim to combine BAP with QCAP and analyze the resulting new integrated problem from the point of view of a transshipment terminal. We solve this problem at the tactical decision level, with the intent of supporting the terminal in its negotiation process with shipping lines, as the number of quay cranes is usually bounded by contracts which are discussed months in advance. Devised analytic tools and quantitative methods allow terminal managers to assign the right value to the QC profiles proposed to shipping lines, considering their impact on the terminal productivity. In addition to profile evaluation, the combined solution of these two problems optimizes the utilization of terminal resources. Alternative objectives are used for this purpose, such as the minimization of total distance covered to move containers, the minimization of ships turnaround time, etc. Starting from a collaboration with the transshipment terminal of Gioia Tauro in Italy, one of the busiest in Europe, we propose a new model for the Tactical Berth Allocation Problem (TBAP) with Quay Crane Assignment, which has been validated on real-world instances provided by the terminal, taking into account a time horizon up to one month. The objective function aims, on the one hand, to maximize the total value of chosen QC profiles and, on the other hand, to minimize the housekeeping costs caused by transshipment flows between ships. Preliminary results obtained through commercial software will be presented and further methodological approaches to the problem, such as decomposition techniques, will be outlined