A heuristic algorithm for yard truck scheduling and storage allocation problems

The yard truck scheduling and the storage allocation are two important decision problems affecting the efficiency of container terminal operations. This paper proposes a novel approach that integrates these two problems into a whole. The objective is to minimize the weighted sum of total delay of requests and the total travel time of yard trucks. Due to the intractability of the proposed problem, a hybrid insertion algorithm is designed for effective problem solutions. Computational experiments are conducted to examine the key factors of the problem and the performance of the proposed heuristic algorithm.     

The integrated yard truck and yard crane scheduling problem: Benders’ decomposition-based methods

This paper proposes a novel integrated model for yard truck and yard crane scheduling problems for loading operations in container terminal. The problem is formulated as a mixed-integer programming model. Due to the computational intractability, two efficient solution methods, based on Benders’ decomposition, are developed for problem solution; namely, the general Benders’ cut-based method and the combinatorial Benders’ cut-based method. Computational experiments are conducted to evaluate the effectiveness of the proposed solution methods.     

Dispatching trucks for drayage operations

We propose a novel model for dispatching trucks given the constraints and sources of uncertainty that arise in drayage operations. The proposed model is designed to minimize the expected cost and is generally applicable to cases including different distributions of random parameters. Numerical examples illustrate this robustness of the model, as well as the potential for reducing the drayage cost by increasing the available storage capacity and permitted number of terminal truck entries. Mathematical results derived within this paper (e.g. expected dwell time) can be used more generally in analyzing transfers in transportation networks under stochastic conditions.     

Space allocating strategies for improving import yard performance at marine terminals

This paper focuses on the organization of the import storage yard at container port terminals. Three new stacking strategies are introduced which take into account the containers’ arrival and departure rates and the storage yard characteristics. A mathematical model based on probabilistic distribution functions is developed to estimate the number of rehandles required to manage an import container yard. The model is applied to the three proposed stacking strategies. Results show that the optimal strategy depends on stacking height and the relationship between vessel headway and container dwell time.     

Joint planning of berth and yard allocation in transshipment terminals using multi-cluster stacking strategy

In this work, a joint planning problem for berth and yard allocation in transshipment terminals is addressed. Multi-cluster stacking strategy is proposed to split each transshipment flow into a number of container clusters and then stack each cluster in different yard blocks. A mixed integer quadratic programming model is formulated to minimize the total distance of exchanging containers between mother vessels and feeders, and the workload imbalance among yard blocks. A novel three-stage heuristic solution approach is developed and extensive numerical experiments are conducted to show the effectiveness of the proposed approach and the benefit of the multi-cluster strategy.     

A hybrid parallel genetic algorithm for yard crane scheduling

This paper aims at postulating a novel strategy in terms of yard crane scheduling. In this study, a dynamic scheduling model using objective programming for yard cranes is initially developed based on rolling-horizon approach. To resolve the NP-complete problem regarding the yard crane scheduling, a hybrid algorithm, which employs heuristic rules and parallel genetic algorithm (PGA), is then employed. Then a simulation model is developed for evaluating this approach. Finally, numerical experiments on a specific container terminal yard are used for system illustration. Computational results suggest that the proposed method is able to solve the problem efficiently.     

Assessment of out-of-state truck activity in California

The continued growth of interstate freight trucking brings with it the potential for inaccuracies in official government statistics on trucks’ road use and pollutant emission contributions. State government agency emission estimates for states within the US commonly rely on in-state truck and fuel use records. Consequently, these records can incompletely reflect overall truck activity and emissions by neglecting the trucks that are registered and/or are fueled out of state. An in-person interview survey of 433 heavy-duty truck drivers was conducted at select points of entry into California to better understand the contribution of out-of-state trucks, their fuel use, and their emissions in California. The results indicate that non-California-registered trucks and non-California-diesel fuel make up approximately 30% of Class 8 heavy-duty truck mileage on California roads. Non-California-registered-truck mileage is disproportionately concentrated in four California air basins that have significant air quality issues.     

Tactical berth and yard template design at container transshipment terminals: A column generation based approach

Quay-side berthing congestion is an emerging challenging issue that arises in busy container transshipment terminals and calls for effective management of terminal operations. This paper tackles the berthing congestion problem by introducing a proactive management strategy from the terminal’s perspective that adjusts the calling schedule of feeder vessels in such a way that the quay-side workload distribution in the temporal dimension can be balanced. Such a schedule template design problem is considered simultaneously with another two tactical level decision problems, berth template design (i.e., determining preferred berthing positions for vessels) and yard template design (i.e., allocating storage yard space to transshipment flows). This highly integrated problem is formulated as a set covering model. Heuristic methods based on column generation are developed to obtain near-optimal solutions in an efficient way. Computational experiments on real-world sized test instances demonstrate the efficiency and effectiveness of the proposed approach.     

The relative importance of factors that influence the break-even distance of intermodal freight transport systems

The break-even distance of an intermodal freight system is a crucial piece of information for shippers as they decide whether to choose a specific freight transport system. It is also important for policy makers who want to demonstrate to shippers that the intermodal system is substantially more beneficial over a certain distance and encourage shippers to use it. However, the break-even distance is highly dependent on market situations. In other words, it is not possible to estimate the definitive break-even distance that is generally applicable. To date, the literature has addressed factors, including costs and distances, that impact the break-even distance without considering the relative importance of each of these factors. This study attempts to address this gap in knowledge by evaluating the relative importance of geometric and cost factors. The former includes drayage distances (i.e., pre- and post-haulage by trucks), truck-only distance, rail distance, the shape of the market area, and the terminal location, while the latter includes the drayage truck rate, the long-distance truck rate, the rail rate, and the terminal handling rate. Finally, by developing a Monte Carlo-based simulation model, the relative importance can be evaluated. The key finding is that the geometric factors and terminal handling costs are not more significant than the transport costs (i.e., rail costs and long-distance trucking costs) in general. Specifically, to shorten the break-even distance, either reducing the rail rate or increasing the truck rate is the most effective strategy. A 1% change in these factors is almost seven times, three times, and twice as effective as a 1% change in the handling costs at terminals, rail distance, and drayage cost, respectively. Furthermore, neither the oval-shaped market area nor a terminal relocation attracts customers to intermodal systems in general. When two options are combined, the synergic effect is significant.     

Determining fixed crane areas in rail–rail transshipment yards

To enable rapid container transshipment between freight trains in modern rail–rail transshipment yards efficient computerized scheduling procedures are indispensable. This paper proposes a dynamic programming approach, which determines yard areas for gantry cranes, so that the workload is evenly spread among cranes and, thus, train processing is accelerated. In a straightforward simulation of transshipment yard operations, the effect of optimal crane areas vs. equally sized areas is studied, the latter being a common real-world policy. The results indicate a remarkable speed-up of train processing if optimal crane areas are applied.     

Modeling hazardous materials risks for different train make-up plans

This paper is concerned with the problem of how to place hazardous material cars in the train assembly process so that the overall derailment risk can be minimized. The approach considers both the probability of railway cars derailing en route by position as well as the risk associated with additional operations in the rail yard using recent US FRA data. The merits of this car placement model are illustrated through a case study of a railway corridor that connects Los Angeles (CA) to Chicago (IL). The case study demonstrates that the proposed risk minimization strategy could be implemented with minimal rail yard operation cost.     

Container storage and transshipment marine terminals

This study addresses the storage arrangement of transshipment containers on a container yard, in order to carry out efficiently the ship handling operations at a terminal where mega-containerships call. An optimization model is specified to investigate the flow of containers from the mega-containership to feeder ships using intermediate storage at the yard. A heuristic based on the lagrangian relaxation is formulated. The quality of the heuristic approach is tested in a number of experiments. In the experiments, various situations are analyzed with respect to mega-containership arrival rates, some strategies for stack arrangements and terminal layouts.     

Effect of block width and storage yard layout on marine container terminal performance

Block widths ranging from two to fifteen rows in a marine container terminal are evaluated by a fully-integrated, discrete event simulation model. Experiments consider dozens of yard configurations and four container terminal settings that are designed to reproduce the microscopic, stochastic, real-time environment at a multiple-berth facility. Results show that the quay crane rate is concave with respect to block width when the yard storage capacity and amount of yard equipment is constant. The optimal block width ranges from 6 to 12 rows depending on the amount of equipment deployed and the size, shape, and throughput of the terminal.     

Truck movement across the Canada–US border: The effects of 9/11 and other factors

The objective of this study is to isolate the effects of the terrorist attacks of 9/11 and the subsequent stringent border security regime on the levels of truck movement across the Canada–US border. A time series analysis, within an econometric system that rendered stationarity and used the seemingly unrelated regression (SUR) estimator, was performed to model these movements. The analysis represents a natural experiment on the variability of cross-border truck movements in the aftermath of 9/11. Annual truck crossing data over the period 1972–2011, disaggregated by the country of registration (US and Canada) and Canadian jurisdictions (provinces) were used in the analysis. The results indicate that in general, 9/11 have had a negative effect on the cross-border movement of Canadian and US trucks, but the impacts were more pronounced in the case of the US trucks. Other interesting results include an increase in the number of US trucks during the period that followed the last US financial crisis. The results also illustrate the importance of GDP in explaining the observed truck movements across the Canada–US border.     

Exploring the relationship between truck load capacity and traffic accidents in the European Union

Applying econometric techniques to EU28 panel data and controlling for explanatory variables such as road types, we find that increased truck load capacity does not necessarily aggravate road traffic safety. Specifically, heavy trucks do not seem to be linked with greater numbers of traffic fatalities/accidents, medium trucks appear to be the worst performers in terms of fatalities, and light trucks seem to be the worst for accidents. In summary, our results clarify the complex relationship between truck load capacity and road safety, pointing to the existence of a negative correlation for accidents per capita and an inverse U-shaped curve for fatalities per capita.     

Negotiating truck arrival times among trucking companies and a container terminal

Congestion of trucks in port areas has created serious environmental and traffic problems in many countries. One of main reasons for congestion is the concentrated arrivals of road trucks at peak hours. A negotiation process for smoothing truck arrivals in peak hours among multiple trucking companies and a terminal is addressed. The negotiation process is to be used for the appointment system for road trucks in container terminals. This paper suggests a mathematical formulation for smoothing the peaks in arrivals considering the inconvenience of trucks from changing their arrival times and the waiting cost of trucks in peak hours. This study proposes a decentralized decision-making model to support the negotiation process between truck companies and the terminal operator. It gives an acceptable solution to every player involved as well as the near optimal solution to the entire system from the global point of view. Numerical experiments are performed to validate the approach in this study.     

Mixed truck delivery systems with both hub-and-spoke and direct shipment

This paper studies a mixed truck delivery system that allows both hub-and-spoke and direct shipment delivery modes. A heuristic algorithm is developed to determine the mode of delivery for each demand and to perform vehicle routing in both modes of deliveries. Computational experiments are carried out on a large set of randomly generated problem instances to compare the mixed system with the pure hub-and-spoke system and the pure direct shipment system. The experiment results show that the mixed system can save around 10% total traveling distance on average as compared with either of the two pure systems.     

A polynomial-time heuristic for the quay crane double-cycling problem with internal-reshuffling operations

One of great challenges in seaport management is how to handle containers under reshuffling, called reshuffles. Repositioning reshuffles in a bay (internal reshuffling) can improve the efficiency of quay cranes and help ports to reduce ship turn-around time. This paper studies the quay crane double-cycling problem with internal-reshuffling operations, and presents a fast solution algorithm. To reduce the number of operations necessary to turn around a bay of a vessel, the problem is first formulated as a new integer program. A polynomial-time heuristic is then developed. The analysis is made on the worst-case error bound of the proposed algorithm. Results are presented for a suite of combinations of problem instances with different bay sizes and workload scenarios. Comparisons are made between our algorithm and the start-of-the-art heuristic. The computational results demonstrate that our model can be solved more efficiently with CPLEX than the model proposed by Meisel and Wichmann (2010), and the proposed algorithm can well solve real-world problem instances within several seconds.     

Scheduling trucks in cross-docking systems: A robust meta-heuristics approach

In a cross-docking system, trucks must be scheduled to minimize the total flow time of the system. This problem is NP-hard, and this study proposes two hybrid meta-heuristics—hybrid simulated annealing and hybrid variable neighborhood search—to solve it by achieving the best sequence of truck pairs. The Taguchi method serves to reveal the best robustness of these algorithms. To demonstrate the effectiveness of the proposed methods, especially for large-sized problems, this study solves various test problems, and the computational results clearly reveal that the proposed methods outperform previous approaches.     

The impact of truck arrival information on container terminal rehandling

This paper uses simulation to evaluate the use of truck arrival information to reduce container rehandles during the import container retrieval process by improving terminal operations. A variety of scenarios with different levels of truck information and various container bay configurations are modeled to explore how the information quality and bay configuration affect the magnitude of benefit. The results demonstrate that a complete arrival sequence is not required to substantially reduce rehandles, significant benefit can be obtained under small amounts of information, the benefits grow with the bay size, and that updating information in real time significantly lowers information requirements.