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

Analysis of marine container terminal gate congestion, truck waiting cost, and system optimization

As world container volume continues to grow and the introduction of 12,000 TEUs plus containerships into major trade routes, the port industry is under pressure to deal with the ever increasing freight volume. Gate congestion at marine container terminal is considered a major issue facing truckers who come to the terminal for container pickup and delivery. Harbor truckers operate in a very competitive environment; they are paid by trip, not by the hours they drive. Gate congestion is not only detrimental to their economic well-being, but also causes environmental pollution. This thesis applies a multi-server queuing model to analyze marine terminal gate congestion and quantify truck waiting cost. In addition, an optimization model is developed to minimize gate system cost. Extensive data collection includes field observations and online camera observation and terminal day-to-day operation records. Comprehensive data analysis provides a solid foundation to support the development of the optimization model. The queuing analysis indicates that there is a substantial truck waiting cost incurred during peak season. Three optimization alternatives are explored. The results prove that optimization by appointment is the most effective way to reduce gate congestion and improve system efficiency. Lastly, it is the recommendation to use the combination of optimization by appointment and productivity improvement to mitigate terminal gate congestion and accommodate the ever growing container volume

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

New Algorithm for Fast Processing RFID System in Container Terminal

The growth of world economic and increasing of trading in most of countries has impact to the number of containers export and import between countries. Some of container terminal is very busy to handle high volume of container movement. Conventional operational procedures have difficulties to handle containers movement then make slow and some issues in terminal operation for container clearance. This paper discus on proposing new algorithm to the current container terminal management system used RFID technology for fast processing and clearance. Container Terminal Management System (CTMS) is a system for port management and interface to the RFID system that used to identify container e-seal, truck and driver identity. Lack of communication and interfacing protocol made slow response during request or reply of message to the gate operator. Proposed algorithm with new procedure of request to CTMS made faster response and avoid inaccuracy of detecting container e-seal. Results of implementation new algorithm have improved to the productivity and efficiency of container terminal. Testing and implementation of this proposed system conducted in a private container terminal in Malaysia

Container Hinterland Drayage - On the Simultaneous Transportation of Containers Having Different Sizes

In an intermodal transportation chain drayage is the term used for the movement by truck of cargo that is filled in a loading unit. The most important intermodal transportation chain is the intermodal container transportation, in which containers represent the loading unit for cargo. Cost effectiveness constitutes a general problem of drayage operations. A major cost driver within container transportation chains is the movement and repositioning of empty containers. The present thesis investigates the potential to reduce drayage costs. Two solution methodologies are developed for operating a fleet of trucks that transports containers of different sizes, which addresses a recent gap in research in seaport hinterland regions

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