Internal Trucks Research Articles

Integrated Scheduling of Yard and Rail Container Handling Equipment and Internal Trucks in a Multimodal Port

Integrated Scheduling of Yard and Rail Container Handling Equipment and Internal Trucks in a Multimodal Port

Yard space allocation of container port based on dual cycle strategy

The dual-cycle operation in loading and unloading operations is widely adopted by container ports around the world. This study addresses the storage space allocation problem of the container yard based on the dual-cycle operation mode, and a mixed integer programming model for storage space allocation in the container yard is established. The container transportation distance is taken as the objective of the optimization model, and practical constraints such as ship operating time demand in ports and yard loading cluster limitations are added. The results of the numerical experiments reveal that the dual-cycle of internal trucks in the yard area can decrease transportation distance of containers, and the space allocation method based on it is more effective than traditional methods. The scenario analysis also provides several management insights for practitioners in container ports and puts forward effective reference suggestions to further solve the bottleneck problem often faced by container ports.

AGV dispatching and bidirectional conflict-free routing problem in automated container terminal

Automated guided vehicles (AGVs) are automated devices that replace internal trucks in container terminals for horizontal container transportation. Compared to internal trucks, AGV has the special characteristic of bidirectional transportation. This characteristic makes AGV change the transport direction without turning around, significantly saving the transport space and time taken up by vehicle transport. However, few studies focus on the bidirectional transportation mode in the AGV scheduling problem to improve the overall efficiency of the automated container terminal (ACT). This study aims at the AGV dispatching and bidirectional conflict-free routing problem. A bi-level mixed integer programming model is proposed, which fully considers equipment coordination, bidirectional conflict-free routing, and import and export container tasks. The bi-level differential evolution algorithm based on the dynamic routing approach is developed to minimize the completion time of all tasks. A series of numerical experiments are conducted to validate the performance of the proposed bidirectional transportation mode and algorithm. The result shows that the efficiency of the bidirectional transportation mode of AGVs is more suitable in the actual ACT operation scenario, and the proposed algorithm can find a better solution within a reasonable amount of time.

A bi-objective optimization for integrated truck operation and storage allocation considering traffic congestion in container terminals

In this work, we are concerned with the traffic congestion issue of internal trucks in busy transshipment container terminals. It is well known that traffic congestion contributes a major part of pollutant emissions in terminals and thus needs to be effectively mitigated. To deal with it, the workload balancing protocol is incorporated and the concept of neighboring subblocks is introduced. Based on this, we study the integrated planning problem of truck operation and storage allocation and a bi-objective optimization model is proposed to minimize the travel distances of trucks and the degree of workload imbalance in the course of moving transshipment containers. A NSGA II based method is designed and extensive experiments are conducted on real-life test instance to show the performance of the solution approach. Trade-off between two objectives is identified and analyzed. Moreover, pollutant emissions caused by trucks’ transportation and traffic congestion are evaluated and discussions are also provided.

Integrated scheduling of yard cranes, external trucks, and internal trucks in maritime container terminal operation

ABSTRACT The operations of yard cranes, external trucks and internal trucks in a maritime container terminal have an important impact on the operational efficiency of the terminal. A multi-objective optimization model is formulated in this paper, with a novel truck-based partition strategy, for a multiple-yard-crane scheduling problem, whose objective is to minimize both total longitudinal distance of yard cranes and total waiting time of internal and external trucks. The proposed model solves the truck assignment subproblem and the yard crane routing subproblem simultaneously to figure out how the trucks are to be served in an optimal manner by each yard crane and the optimal rank of each truck by which each yard crane provides container handling services in order. The effectiveness of the integrated truck-based and block-based scheduling strategies is validated by comparing with the existing strategies. Both the integrated block-based and the integrated truck-based scheduling strategies balance the two conflicting objectives better than the prioritized scheduling strategy and the first-come-first-served scheduling strategy. Numerical experiments shows that the advantage of the two integrated strategies is related to the ratio of the number of yard cranes to the number of container blocks. Some implications for port operation policy are also discussed.

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.

Research on scheduling optimization of internal trucks for inter-terminal transportation

Based on the operation mode of inter-terminal transportation in a container port, an optimization method of internal trucks scheduling was proposed to cooperate among multiple terminals in a port. In order to minimize the remaining workload of each terminal, a mixed integer programming model for internal trucks scheduling optimization was established by considering the transportation time and energy consumption of internal trucks. The improved genetic algorithm was used to solve the model, and an example was given to verify the validity of the model. The results show that the scheduling optimization model based on inter-terminal transportation mode can effectively reduce the total operating cost of each terminal and improve the utilization rate of internal trucks.

A new vocation queuing model to optimize truck appointments and yard handling-equipment use in dual transactions systems of container terminals

In a dual transaction at a marine terminal, an external truck drops off one container and picks up another on a single trip. To ensure a successful dual transaction operation and smooth external truck arrivals, a bi-objective mixed integer programming model is developed that optimizes the allocation of appointment quotas simultaneously with the deployment of (yard) cargo handling equipment. Our model addresses the challenges posed by the different types of truck movement in the terminal, i.e., delivery, pickup, and dual transaction. These require different handling equipment, various deadlines, and multiple priorities. To estimate the queuing length of external trucks in single or dual transactions (as well as that of internal trucks), a novel three-level vocation queuing model is set up. For the bi-objectives optimization, we propose a revised non-dominated genetic algorithm to obtain the approximate optimal solution. Experimental results prove the efficiency and effectiveness of the method. It shows that the newly built vocation queuing model can estimate the prioritized queuing process more effectively in three respects: a) the 3-level queuing; b) discrete truck arrivals in the queuing system; c) non-interruption of servers. Our quota optimization design improves the model’s applicability to real cases, especially in the case of dual transactions. It is demonstrated that the method proposed in the paper could help terminal operators allocate quotas and simultaneously match the capacity of yard handling, thus improving truck services and terminal profitability.

Benders decomposition for internal truck renewal decision in green ports

ABSTRACT To effectively decrease emissions and pollution emitted by equipment in container ports, many ports began to update equipment using diesel fuels to achieve the aim of green ports. This paper studies an internal truck renewal problem in container ports and proposes a two-stage stochastic programming model to optimally determine internal truck composition optimization adjustment including three renewal modes, i.e. purchasing, retrofitting, and chartering. An exact solution procedure based on Benders decomposition accelerating by Pareto-optimal cuts is developed for the proposed model. Given the problem background of Shanghai Yangshan Deep Water Port, comprehensive computational experiments are carried out to verify the effectiveness of the proposed mathematical model and the performance of the solution approach. According to the numerical experiments, some suggestions for the management of renewing internal trucks in green ports are summarized at the end of the paper.

Allocation and Scheduling of Handling Resources in the Railway Container Terminal Based on Crossing Crane Area

The integrated allocation and scheduling of handling resources are crucial problems in the railway container terminal (RCT). We investigate the integrated optimization problem for handling resources of the crane area, dual-gantry crane (GC), and internal trucks (ITs). A creative handling scheme is proposed to reduce the long-distance, full-loaded movement of GCs by making use of the advantages of ITs. Based on this scheme, we propose a flexible crossing crane area to balance the workload of dual-GC. Decomposing the integrated problem into four sub-problems, a multi-objective mixed-integer programming model (MIP) is developed. By analyzing the characteristic of the integrated problem, a three-layer hybrid heuristic algorithm (TLHHA) incorporating heuristic rule (HR), elite co-evolution genetic algorithm (ECEGA), greedy rule (GR), and simulated annealing (SA) is designed for solving the problem. Numerical experiments were conducted to verify the effectiveness of the proposed model and algorithm. The results show that the proposed algorithm has excellent searching ability, and the simultaneous optimization scheme could ensure the requirements for efficiency, effectiveness, and energy-saving, as well as the balance rate of dual-GC.

Combined Internal Trucks Allocation of Multiple Container Terminals with Hungarian Algorithm

Yang, X.; Zhao, N., and Yu, S., 2020. Combined internal trucks allocation of multiple container terminals with Hungarian Algorithm. In: Yang, Y.; Mi, C.; Zhao, L., and Lam, S. (eds.), Global Topics and New Trends in Coastal Research: Port, Coastal and Ocean Engineering. Journal of Coastal Research, Special Issue No. 103, pp. 923–927. Coconut Creek (Florida), ISSN 0749-0208.With the rising efficiency demand and intelligence trend of the container terminals (CTs), horizontal transportation could be a vital bottle neck of terminal operations. In artificial terminals, Internal trucks (ITs) is the most common and versatile horizontal equipment, the efficiency of ITs affects horizontal transportation efficiency greatly. With sharing ITs among multiple CTs located nearby, the IT resource could be allocated in a wider range to further improve handling efficiency. In this paper, we proposed a multi-objective MIP model for IT allocation, and a Hungarian Algorithm is introduced to solve the problem in a preferable period of time. Numerical experiment shows that, the proposed model and Hungarian Algorithm are efficient to achieve the optimal allocation solution.

Energy-Efficient and Integrated Allocation of Berths, Quay Cranes, and Internal Trucks in Container Terminals

Despite a significant number of studies that have focused on the operational efficiency of container terminals, existing literature has paid little attention to improving energy efficiency, e.g., energy consumption and negative externalities in container terminals. Most researchers consider energy-saving goals when allocating berths and quay cranes to vessels, assuming that internal trucks are in sufficient supply. Furthermore, recent studies have revealed that shortage of internal trucks has become an issue that greatly affects the operational and energy efficiencies of container terminals. This work presents a planning model that integrates berth allocation, quay crane assignment, and internal truck assignment problems. The developed model contributes to existing literature by including energy-saving goals in the integrated planning of these problems, as well as including important realistic factors such as shortages of internal trucks and handling time estimations, thus producing a reliable handling plan that achieves energy and cost savings without additional truck investment. To solve realistic problems, a Lagrangian relaxation-based method is developed. Furthermore, the benefits of the developed approach are demonstrated by comparing it to an existing approach. On average, our approach could improve the solutions of the integrated problem with different numbers of internal trucks by 6% compared to the solutions obtained using the existing approach.

Bi-objective optimization for integrating quay crane and internal truck assignment with challenges of trucks sharing

Due to both the rapid growth of world and the expansion of the flow of container shipment, a maritime container terminal plays a vital role in global coverage of supply chain. In this market, because shipping is growing fast, container terminals should be able to serve the vessels in the shortest possible time. Alternatively, the limited availability of operational facilities, such as internal trucks, makes servicing more complicated in container terminals. Therefore, this study aimed to integrate the assignment of quay cranes in container terminals and internal truck sharing assignment among them. For this purpose, a bi-objective optimization model is developed. In the proposed model, several assignment phases, including the assignments of the vessel to container terminals, cranes to terminals, cranes to vessels and trucks to cranes are performed. The model also seeks to increase and improve the efficiency and effectiveness of internal trucks by sharing them among different terminals, so that there is an appropriate balance between the volume of workloads of the terminals and the trucks in question. The first objective function in the proposed model seeks to minimize operational costs and the second objective function seeks to minimize the maximum overflowed workload in the terminals. Furthermore, in order to solve the proposed model, two meta-heuristic multi-objective algorithms, including modified non-dominated sorting genetic algorithm-II (MNSGA-II) and modified multi-objective particle swarm optimization (MMOPSO) are presented. Several numerical examples have been investigated and analyzed to show the accuracy of the proposed model and the methods. In addition, the results demonstrated that the simultaneous consideration of the assignments and the sharing of trucks would reduce the remaining workload in the terminals.

Integrated Scheduling of Rail-Mounted Gantry Cranes, Internal Trucks and Reach Stackers in Railway Operation Area of Container Terminal

In this paper, the integrated scheduling of handling equipment at the railway handling area in container terminals is studied, where rail-mounted gantry cranes, internal trucks, and reach stackers are deployed. In the course of the handling operation, loading and unloading containers are handled simultaneously. The handling process is first studied and some scheduling schemes are put forward. Based on the analysis, the problem is formulated as a mixed-integer programming model, with the objectives of minimizing the makespan and the total waiting time of all equipment. Then, to solve the problem, a genetic algorithm is employed, where the first available machine rule is applied in the selection of trucks and reach stackers. Sets of numerical experiments are conducted to verify the effect of the proposed algorithm. Based on the results of experiments, some key indicators are calculated and the effects of different equipment configuration schemes are studied.

Optimization of truck appointments in container terminals

Truck appointment has proved to be an efficient tool in reducing congestion at container terminals. To make a reasonable appointment quota plan, it is necessary to take terminal operations into consideration. We develop a novel approach (model) for optimizing a truck appointment system with the objective of decreasing external trucks’ waiting times, at the gate and yard, and internal trucks’ waiting times at the yard. The vacation queuing model is used to describe the coordinated service process of yard cranes. Based on non-stationary queuing theory, truck waiting times are estimated more accurately. Numerical experiments are conducted to illustrate the validity of the model and algorithm. Results show that the model reflects the characteristics of the service process of yard cranes and it improves the calculation accuracy of the truck waiting time.

Simultaneous assignment of quay cranes and internal trucks in container terminals

This paper studies the assignment of quay cranes to the berthed vessels and the assignment of internal trucks to each quay crane at container terminals. Previous studies have either dealt with the two planning decisions separately or ignored the internal truck capacity constraint when determining the assignments of the quay cranes, thus producing a handling plan of poor overall quality. This paper addresses the assignment of quay cranes and internal trucks simultaneously. A mixed integer programming model is used to assign quay cranes to each vessel and assign internal trucks to each quay crane. The proposed model is validated against an existing model from literature. Numerical experiments with the proposed model using actual container terminal data show that the proposed model reduces the average berthing stay per vessel compared to the existing models in literature in case of limited availability of internal trucks.

A Lagrangian relaxation approach for the integrated quay crane and internal truck assignment in container terminals

The planning decisions related to the assignment of quay cranes and internal trucks to the berthed vessels in container terminals are typically made independently. However, a more reliable estimation for the vessels' handling times as well as the truck requirements can be achieved when such planning decisions are made simultaneously. This paper presents a mathematical model that can be used to solve the quay crane assignment problem, the specific quay crane assignment problem and the assignment of internal trucks to each quay crane simultaneously. The proposed model considers important practical aspects such as the limited availability and operation cost of the internal trucks. A Lagrangian relaxation, and subgradient optimisation procedure-based heuristic is proposed for the model. The performance of the proposed heuristic algorithm is investigated using actual container terminal data.

An Intelligent Storage Determining Method for Inbound Containers in Container Terminals

ABSTRACT Yang, X.; Zhao, N.; Bian, Z.; Chai, J., and Mi, C., 2015. An intelligent storage determining method for inbound containers in container terminals. In this paper, the container Stacking Position Determination Problem (SPDP) for inbound containers in the process of vessel loading and unloading activities is discussed, specifically focusing on the storage space allocation problem (SSAP) in container terminals. The process of positioning inbound containers is investigated and analyzed based on an advanced handling strategy, namely assigning quay cranes in their full utilization with the aim of “Full In & Full Out” that is proposed for internal trucks, where intense loading and unloading activities are considered at the same time. A multi-objective integer programming model (MOIPM) is then put forward based on the idea of real-time strategic planning. For the solution, a genetic algorithm (GA) is employed to address the formulated problem. In addition to the effectiveness and reliability of the propos...

Integrated internal truck, yard crane and quay crane scheduling in a container terminal considering energy consumption

Container terminals mainly include three types of handling equipment, i.e., quay cranes (QCs), internal trucks (ITs) and yard cranes (YCs). Due to high cost of the handling equipment, container terminals can hardly purchase additional handling equipment. Therefore, the reasonable scheduling of these handling equipment, especially coordinated scheduling of the three types of handling equipment, plays an important role in the service level and energy-saving of container terminal. This paper addresses the problem of integrated QC scheduling, IT scheduling and YC scheduling. Firstly, this problem is formulated as a mixed integer programming model (MIP), where the objective is to minimize the total departure delay of all vessels and the total transportation energy consumption of all tasks. Furthermore, an integrated simulation-based optimization method is developed for solving the problem, where the simulation is designed for evaluation and optimization algorithm is designed for searching solution space. The optimization algorithm integrates genetic algorithm (GA) and particle swarm optimization (PSO) algorithm, where the GA is used for global search and the PSO is used for local search. Finally, numerical experiments are conducted to verify the effectiveness of the proposed method. The results show that the proposed method can coordinate the scheduling of the three types of handling equipment and can realize the optimal trade-off between time-saving and energy-saving.

A decision support method for internal truck employment

Purpose – The purpose of this paper is to propose a model that determines the strategy of owning and renting trucks in combinations with internal truck scheduling and storage allocation problems in container terminals. Design/methodology/approach – To deal with this complicated problem, a two-level heuristic approach is developed, in which the integration problem is decomposed into two levels. The first level determines the daily operations of the internal trucks, while the second level determines the truck employment strategy based on the calculation in the first level. Findings – The results show that: even if the using cost of owned yard trucks is much lower than the cost of rented yard tucks, terminal companies should not purchase too many trucks when the purchasing price is high. In addition, the empirical truck employment strategies, which are purchasing all the trucks or renting all the trucks, are not cost-effective when compared with the proposed yard truck employment strategy. Originality/value – The paper provides a novel insight for the internal truck employment strategy in container terminals which is the determination of the strategy of employing renting and outsourcing yard trucks to meet operational daily transportation requirements and minimize the long-term cost of employing yard trucks. A mathematical model is proposed to deal with the practical problem. Also, this study presents better solution than empirical method for employing different types of yard truck. Thus, in order to obtain more benefit, terminal companies should employ the proposed yard truck employment strategy.