Collaborative truck scheduling and appointments for trucking companies and container terminals

Appointment systems for truck arrivals at container terminals have been applied in many ports to reduce truck congestion. This study suggests a new appointment process by which trucking companies and terminals collaboratively determine truck operation schedules and truck arrival appointments. This study formulates a mathematical model involving a sub-problem for each trucking company to determine the optimal dispatching schedules for trucks and the other sub-problem for the terminal to estimate the expected truck system time in each time interval. An iterative collaboration process is proposed based on a decomposed mathematical formulation. Numerical experiments are conducted to investigate the performance of the decision process and the robustness of the process in practical operation conditions.     

The impact of job assignment rules for straddle carriers on the throughput of container terminals

Straddle carriers represent a critical resource in the handling of containers within a container terminal. It is essential that they are deployed in an as efficient manner as possible. The research presented in this paper is motivated by the need to critically evaluate job assignment rules for straddle carriers that operate in a multiple straddle environment. This is achieved by developing a discrete event simulation model using industrial simulation software to model a container terminal located in Melbourne, Australia. The model accounts for variables such as the number of straddle carriers needed, the speed of straddle carriers, the arrival rate of trucks, and the job assignment rule. A principal finding of the study is that increasing the number of straddles in the present set‐up from 6 to 7 has a negligible effect on daily throughput. However, an increase in the number of straddles to 7 is expected to have a profound effect on reducing the average waiting time of trucks within the terminal from over 16 minutes to under 9 minutes, a decrease of 46.5%. However, a further increase in the number of straddles results in no further increase in daily throughput. It was observed that the throughput of the terminal is very sensitive to the speeds at which straddles travel. The management of the terminal has proposed a new heuristic job assignment rule for straddles, because the present rule does not assign the jobs to straddles closest to the truck requesting to load or unload a container. As a result a new heuristic job assignment rule was tested. The simulation results revealed that both the old and new rules performed equally well using performance indicators such as average container flow time, daily throughput, average waiting time of jobs, number of jobs in the queue, and straddle utilisation. Therefore, the new rule will not improve these performance measures if implemented     

Optimizing coordinated transfer with probabilistic vehicle arrivals and passengers' walking time

Supporting efficient connections by synchronizing vehicle arrival time and passengers' walking time at a transfer hub may significantly improve service quality, stimulate demand, and increase productivity. However, vehicle travel times and walking times in urban settings often varies spatially and temporally due to a variety of factors. Nevertheless, the reservation of slack time and/or the justification of vehicle arrival time at the hub may substantially increase the success of transfer coordination. To this end, this paper develops a model that considers probabilistic vehicle arrivals and passengers walking speeds so that the slack time and the scheduled bus arrival time can be optimized by minimizing the total system cost. A case study is conducted in which the developed model is applied to optimize the coordination of multiple bus routes connecting at a transfer station in Xi'an, China. The relationship between decision variables and model parameters, including the mean and the standard deviation of walking time, is explored. It was found that the joint impact of probabilistic vehicle arrivals and passengers' walking time significantly affects the efficiency of coordinated transfer. The established methodology can essentially be applied to any distribution of bus arrival and passenger walking time. Copyright © 2017 John Wiley & Sons, Ltd.     

A slack arrival strategy to promote flex-route transit services

Flex-route transit, which combines the advantages of fixed-route transit and demand-responsive transit, is one of the most promising options in low-demand areas. This paper proposes a slack arrival strategy to reduce the number of rejected passengers and idle time at checkpoints resulting from uncertain travel demand. This strategy relaxes the departure time constraints of the checkpoints that do not function as transfer stations. A system cost function that includes the vehicle operation cost and customer cost is defined to measure system performance. Theoretical and simulation models are constructed to test the benefits of implementing the slack arrival strategy in flex-route transit under expected and unexpected demand levels. Experiments over a real-life flex-route transit service show that the proposed slack arrival strategy could improve the system performance by up to 40% with no additional operating cost. The results demonstrate that the proposed strategy can help transit operators provide more cost-efficient flex-route transit services in suburban and rural areas.     

A study of economic efficiency in port security inspection

The purpose of this paper is to study an economic efficiency for the prediction of additional truck turnaround time and for determining the number of the port security inspection equipment required at a terminal inspection station. The economic efficiency with six base models was developed to assist terminal operators' decision‐making. In addition, this study developed an optimal procedure that terminal operators could use to optimally run in terms of various statistics processes including exponential, deterministic, and others, seeking a solution that was beneficial for both terminal operators and truckers. As a result of this research of the additional cargo turnaround time for port security delay, the following conclusion can be drawn and made. The average additional delay time in the inspection station is very dependent on the inspection rate of the lower stage. The higher weighted inspection time based on raising security level allows less number of trucks to be inspected, which will derive high delay in the inspection station. Increase of rate of Green Lane usage will allow a decrease in the arrival rate, which may derive improvement of inspection equipment efficiency and average delay time at the inspection station. In multiple stage model, total number of trucks and delay time very closely follow those of low inspection stage rate and number of inspection units. Free Lane is to be followed by Customs‐Trade Partnership Against Terrorism and standardization of customs, packing, loading and unloading, documents, procedure, and exchange working in each country. Copyright © 2012 John Wiley & Sons, Ltd.     

Cranes scheduling in frame bridges based automated container terminals

This paper investigates crane scheduling problems for a new type of automated container terminal system, which is based on multi-storey frame bridges. For the new design concept, this paper studies how to schedule two types of cranes, i.e., quay cranes and bridge cranes that transfer containers between different storeys. The schedules of these two types of cranes impact the operation efficiency of the terminal system. Mathematical models are proposed for the two scheduling problems. Meta-heuristics are developed to solve them. Numerical experiments are conducted to validate the effectiveness of the proposed models and the efficiency of the proposed solution method.     

Improving recovery-to-optimality robustness through efficiency-balanced design of timetable structure

To improve the service quality of the railway system (e.g., punctuality and travel times) and to enhance the robust timetabling methods further, this paper proposes an integrated two-stage approach to consider the recovery-to-optimality robustness into the optimized timetable design without predefined structure information (defined as flexible structure) such as initial departure times, overtaking stations, train order and buffer time. The first-stage timetabling model performs an iterative adjustment of all departure and arrival times to generate an optimal timetable with balanced efficiency and recovery-to-optimality robustness. The second-stage dispatching model evaluates the recovery-to-optimality robustness by simulating how each timetable generated from the first-stage could recover under a set of restricted scenarios of disturbances using the proposed dispatching algorithm. The concept of recovery-to-optimality is examined carefully for each timetable by selecting a set of optimally refined dispatching schedules with minimum recovery cost under each scenario of disturbance. The robustness evaluation process enables an updating of the timetable by using the generated dispatching schedules. Case studies were conducted in a railway corridor as a special case of a simple railway network to verify the effectiveness of the proposed approach. The results show that the proposed approach can effectively attain a good trade-off between the timetable efficiency and obtainable robustness for practical applications.     

Time control point strategy coupled with transfer coordination in bus schedule design

A schedule consisting of an appropriate arrival time at each time control point can ensure reliable transport services. This paper develops a novel time control point strategy coupled with transfer coordination for solving a multi‐objective schedule design problem to improve schedule adherence and reduce intermodal transfer disutility. The problem is formulated using a robust mixed‐integer nonlinear programming model. The mixed‐integer nonlinear programming model is equivalently transformed into a robust mixed‐integer linear programming model, which is then approximated by a deterministic mixed‐integer linear programming model through Monte Carlo simulation. Thus, the optimal scheduled arrival time at each time control point can be precisely obtained using cplex . Numerical experiments based on three bus lines and the mass rapid transit system in Singapore are presented, and the results show that the schedule determined using the developed model is able to provide not only reliable bus service but also a smooth transfer experience for passengers. Copyright © 2016 John Wiley & Sons, Ltd.     

Intermodal Transit System Coordination

In urban areas where transit demand is widely spread, passengers may be served by an intermodal transit system, consisting of a rail transit line (or a bus rapid transit route) and a number of feeder routes connecting at different transfer stations. In such a system, passengers may need one or more transfers to complete their journey. Therefore, scheduling vehicles operating in the system with special attention to reduce transfer time can contribute significantly to service quality improvements. Schedule synchronization may significantly reduce transfer delays at transfer stations where various routes interconnect. Since vehicle arrivals are stochastic, slack time allowances in vehicle schedules may be desirable to reduce the probability of missed connections. An objective total cost function, including supplier and user costs, is formulated for optimizing the coordination of a general intermodal transit network. A four-stage procedure is developed for determining the optimal coordination status among routes at every transfer station. Considering stochastic feeder vehicle arrivals at transfer stations, the slack times of coordinated routes are optimized, by balancing the savings from transfer delays and additional cost from slack delays and operating costs. The model thus developed is used to optimize the coordination of an intermodal transit network, while the impact of a range of factors on coordination (e.g., demand, standard deviation of vehicle arrival times, etc) is examined.     

Flight schedule punctuality control and management: a stochastic approach

The insufficiency of infrastructure capacity in an air transport system is usually blamed for poor punctuality performance when implementing flight schedules. However, investigations have revealed that ground operations of airlines have become the second major cause of flight delay at airports. A stochastic approach is used in this paper to model the operation of aircraft turnaround and the departure punctuality of a turnaround aircraft at an airport. The aircraft turnaround model is then used to investigate the punctuality problem of turnaround aircraft. Model results reveal that the departure punctuality of a turnaround aircraft is influenced by the length of scheduled turnaround time, the arrival punctuality of inbound aircraft as well as the operational efficiency of aircraft ground services. The aircraft turnaround model proposed is then employed to evaluate the endogenous schedule punctuality of two turnaround aircraft. Model results, when compared with observation data, show that the operational efficiency of aircraft ground services varies among turnarounds. Hence, it is recommended that the improvement of departure punctuality of turnaround aircraft may be achieved from two approaches: airline scheduling control and the management of operational efficiency of aircraft ground services.     

Model based urban traffic control,part II: Coordinated model predictive controllers

The present paper describes how to use coordination between neighbouring intersections in order to improve the performance of urban traffic controllers. Both the local MPC (LMPC) introduced in the companion paper (Hao et al., 2018) and the coordinated MPC (CMPC) introduced in this paper use the urban cell transmission model (UCTM) (Hao et al., 2018) in order to predict the average delay of vehicles in the upstream links of each intersection, for different scenarios of switching times of the traffic lights at that intersection. The feedback controller selects the next switching times of the traffic light corresponding to the shortest predicted average delay. While the local MPC (Hao et al., 2018) only uses local measurements of traffic in the links connected to the intersection in comparing the performance of different scenarios, the CMPC approach improves the accuracy of the performance predictions by allowing a control agent to exchange information about planned switching times with control agents at all neighbouring intersections. Compared to local MPC the offline information on average flow rates from neighbouring intersections is replaced in coordinated MPC by additional online information on when the neighbouring intersections plan to send vehicles to the intersection under control. To achieve good coordination planned switching times should not change too often, hence a cost for changing planned schedules from one decision time to the next decision time is added to the cost function. In order to improve the stability properties of CMPC a prediction of the sum of squared queue sizes is used whenever some downstream queues of an intersection become too long. Only scenarios that decrease this sum of squares of local queues are considered for possible implementation. This stabilization criterion is shown experimentally to further improve the performance of our controller. In particular it leads to a significant reduction of the queues that build up at the edges of the traffic region under control. We compare via simulation the average delay of vehicles travelling on a simple 4 by 4 Manhattan grid, for traffic lights with pre-timed control, traffic lights using the local MPC controller (Hao et al., 2018), and coordinated MPC (with and without the stabilizing condition). These simulations show that the proposed CMPC achieves a significant reduction in delay for different traffic conditions in comparison to these other strategies.     

Optimization of terminal airspace operation with environmental considerations

The rapid growth in air traffic has resulted in increased emission and noise levels in terminal areas, which brings negative environmental impact to surrounding areas. This study aims to optimize terminal area operations by taking into account environmental constraints pertaining to emission and noise. A multi-objective terminal area resource allocation problem is formulated by employing the arrival fix allocation (AFA) problem, while minimizing aircraft holding time, emission, and noise. The NSGA-II algorithm is employed to find the optimal assignment of terminal fixes with given demand input and environmental considerations, by incorporating the continuous descent approach (CDA). A case study of the Shanghai terminal area yields the following results: (1) Compared with existing arrival fix locations and the first-come-first-serve (FCFS) strategy, the AFA reduces emissions by 19.6%, and the areas impacted by noise by 16.4%. AFA and CDA combined reduce the emissions by 28% and noise by 38.1%; (2) Flight delays caused by the imbalance of demand and supply can be reduced by 72% (AFA) and 81% (AFA and CDA) respectively, compared with the FCFS strategy. The study demonstrates the feasibility of the proposed optimization framework to reduce the environmental impact in terminal areas while improving the operational efficiency, as well as its potential to underpin sustainable air traffic management.     

A container terminal simulation model with animation capabilities

The objective of this paper is to introduce a computer simulation model with on-screen animation graphics, which can simulate the operations of a container terminal equipped with straddle carriers. The movements of the equipment are simulated as realistically as possible, to include time losses due to the mismatch in the sequence of equipment movements and to traffic congestion. Trucks are normally served in a specified area, but in some cases, straddle carrier drivers can call the truck to be served directly in the container storage areas. The experience of operators is incorporated in the model, in the form of a knowledge base, that is used to simulate the above process and determine the service discipline. The model was designed to evaluate different configurations (changes in yard layout, equipment number and productivity, truck arrival pattern and service discipline) of the simulated system. The proposed model was used to examine the differences between “the observed” operations strategy and the strategy dictated by the operational rules of the port of Piraeus. The results indicate that “the observed” strategy leads to shorter truck service time but increase the traffic conflicts in the terminal's internal transport networks.     

Bus dispatching at timed transfer transit stations using bus tracking technology

A timed transfer terminal synchronizes the arrival of incoming vehicles with the departure of outgoing vehicles so as to minimize transfer delays. Most bus timed transfer terminals follow fixed schedules, and do not utilize intelligent transportation systems for vehicle tracking and control. This paper reviews technologies that enable real-time control of timed transfer. We evaluate the benefits of tracking bus locations and executing dynamic schedule control through the simulation of a generic timed transfer terminal under a range of conditions. Based on empirical data collected by the Los Angeles County/Metropolitan Transit Agency, we found delay over segments of long-headway bus lines to be negatively correlated with lateness at the start of the segment, indicating that buses have a tendency to catch up when they fall behind schedule. The simulation analysis showed that the benefit of bus tracking is most significant when one of the buses experiences a major delay, especially when there is a small number of connecting buses.     

Port privatization,efficiency and competitiveness: Some empirical evidence from container ports (terminals)

Few studies have investigated the quantitative relationship between port ownership structure and port efficiency with mixed results. This study applies a stochastic frontier model proposed by Battese and Coelli [Battese, G.E., Coelli, T.J., 1995. A model for technique inefficiency effects in a stochastic frontier production function for panel data. Empirical Economics 20, 325–332], which incorporates the inefficiency effect, to show whether port privatization is a necessary strategy for ports to gain a competitive advantage. While this stochastic frontier model has been used to a wide number of industries where the technical inefficiency effect is required, this method has rarely been employed to port industry. This study also investigates the determinants of port competitiveness. Both the principal component analysis (PCA) and the linear regression model are used to examine the effects of identified key factors on port competitiveness. Based on a sample of selected container terminals around the world, the results of this study have shown that private sector participation in the port industry to some extent can improve port operation efficiency, which will in turn increase port competitiveness. Another important determinant of port competitiveness is the adaptability to the customers’ demand. All these results provide some policy implications and guidance for port authorities and port operators in formulating effective strategies to improve their competitiveness vis-à-vis rivals.     

Multi-modal traffic signal control with priority,signal actuation and coordination

Both coordinated-actuated signal control systems and signal priority control systems have been widely deployed for the last few decades. However, these two control systems are often conflicting with each due to different control objectives. This paper aims to address the conflicting issues between actuated-coordination and multi-modal priority control. Enabled by vehicle-to-infrastructure (v2i) communication in Connected Vehicle Systems, priority eligible vehicles, such as emergency vehicles, transit buses, commercial trucks, and pedestrians are able to send request for priority messages to a traffic signal controller when approaching a signalized intersection. It is likely that multiple vehicles and pedestrians will send requests such that there may be multiple active requests at the same time. A request-based mixed-integer linear program (MILP) is formulated that explicitly accommodate multiple priority requests from different modes of vehicles and pedestrians while simultaneously considering coordination and vehicle actuation. Signal coordination is achieved by integrating virtual coordination requests for priority in the formulation. A penalty is added to the objective function when the signal coordination is not fulfilled. This “soft” signal coordination allows the signal plan to adjust itself to serve multiple priority requests that may be from different modes. The priority-optimal signal timing is responsive to real-time actuations of non-priority demand by allowing phases to extend and gap out using traditional vehicle actuation logic. The proposed control method is compared with state-of-practice transit signal priority (TSP) both under the optimized signal timing plans using microscopic traffic simulation. The simulation experiments show that the proposed control model is able to reduce average bus delay, average pedestrian delay, and average passenger car delay, especially for highly congested condition with a high frequency of transit vehicle priority requests.     

长途跨线高速列车直达与中转选择问题

我国快速客运网基本形成,长途跨线列车直达与中转选择对于高速列车开行方案设计至关重要。为提升长途跨线高速列车开行效益和服务品质,按长途跨线列车直达与中转方式对比的思路,以旅客出行需求、基础设施能力、移动设备能力等多方面因素对长途跨线列车开行方式的影响为约束条件,研究长途跨线列车直达与中转选择模型及求解方法。选取2025年15个长途跨线起讫点为对象进行案例研究,提出D站—E站、F站—D站等9个起迄点之间开行长途跨线直达列车的建议方案,研究表明直达与中转换乘选择模型能够解决长途跨线列车开行方案编制问题。     

A simulation model of reliable schedule design for a fixed transit route

This paper describes a simulation model of schedule design for a fixed transit route adopting the holding control strategy. The model is capable of determining the locations of time points and the amount of slack time allocated to each time point by minimizing the total cost associated with the schedule. The optimization is carried out through a process, which combines a heuristic search, enumeration, and population ranking and selection techniques. Examples showing applications and potential savings of the proposed model are given. It is shown that the model can serve as a practical tool for designing reliable, economical as well as operational transit schedules.     

Storage space allocation in container terminals

Container terminals are essential intermodal interfaces in the global transportation network. Efficient container handling at terminals is important in reducing transportation costs and keeping shipping schedules. In this paper, we study the storage space allocation problem in the storage yards of terminals. This problem is related to all the resources in terminal operations, including quay cranes, yard cranes, storage space, and internal trucks. We solve the problem using a rolling-horizon approach. For each planning horizon, the problem is decomposed into two levels and each level is formulated as a mathematical programming model. At the first level, the total number of containers to be placed in each storage block in each time period of the planning horizon is set to balance two types of workloads among blocks. The second level determines the number of containers associated with each vessel that constitutes the total number of containers in each block in each period, in order to minimize the total distance to transport the containers between their storage blocks and the vessel berthing locations. Numerical runs show that with short computation time the method significantly reduces the workload imbalance in the yard, avoiding possible bottlenecks in terminal operations.     

A model for national freight flows,distribution centers,empty trucks and urban truck movements

Trucks travel both short distances for local deliveries and long distances for transporting goods across the country. Often their travel behavior is tour-based, they run under tight schedules and under curfew on selected roads. Despite these differences from personal travel, in practice truck models largely follow person travel methods. To overcome this shortcoming, a two-layer truck model is developed for the Chicago Metropolitan Area. Long-distance trucks are driven by commodity flows, with distribution centers, rail yards, marine ports and airports being represented explicitly. Empty trucks are accounted for as well. For the short-distance truck model, a novel parameter estimation method makes use of limited data to derive region-specific parameters. The model is fully operational and validates reasonably well against traffic counts.