Nathan Huynh

Analysis of driver injury severity in rural single-vehicle crashes

Rural roads carry less than fifty percent of the traffic in the United States. However, more than half of the traffic accident fatalities occurred on rural roads. This research focuses on analyzing injury severities involving single-vehicle crashes on rural roads, utilizing a latent class logit (LCL) model. Similar to multinomial logit (MNL) models, the LCL model has the advantage of not restricting the coefficients of each explanatory variable in different severity functions to be the same, making it possible to identify the impacts of the same explanatory variable on different injury outcomes. In addition, its unique model structure allows the LCL model to better address issues pertinent to the independence from irrelevant alternatives (IIA) property. A MNL model is also included as the benchmark simply because of its popularity in injury severity modeling. The model fitting results of the MNL and LCL models are presented and discussed. Key injury severity impact factors are identified for rural single-vehicle crashes. Also, a comparison of the model fitting, analysis marginal effects, and prediction performance of the MNL and LCL models are conducted, suggesting that the LCL model may be another viable modeling alternative for crash-severity analysis.

An efficient genetic algorithm for solving the quay crane scheduling problem

This paper addresses the quay crane scheduling problem (QCSP), which has been shown to be NP-complete. For this reason, a number of studies have proposed the use of genetic algorithm (GA) as the means to obtain the solution in reasonable time. This study extends the research in this area by utilizing the GA that is available in the latest version of Global Optimization Toolbox in MATLAB 7.13 to facilitate development. It aims to improve the efficiency of the GA search by (1) using an initial solution based on the S-LOAD rule developed by Sammarra, Cordeau, Laporte, and Monaco (2007), (2) using a new approach for defining the chromosomes (i.e., solution representation) to reduce the number of decision variables, and (3) using new procedures for calculating tighter lower and upper bounds for the decision variables. The effectiveness of the developed GA is tested using several benchmark instances proposed by Meisel and Bierwirth (2011). Compared to the current best-known solutions, experimental results show that the proposed GA is capable of finding the optimal or near-optimal solution in significantly shorter time for larger problems.

Storage space allocation at marine container terminals using ant-based control

Highlights? We developed an ant-based model for the storage space allocation problem (SSAP). ? Our decentralized model is the first of its kind developed to address the SSAP. ? Our model provides a scalable, real-time, adaptive and efficient approach. This paper presents a novel approach for allocating containers to storage blocks in a marine container terminal. We model the container terminal as a network of gates, yard blocks and berths on which export and import containers are considered as bi-directional traffic. For both export and import containers, the yard blocks are the intermediate storage points between gates (landside) and berths (waterside). Our model determines the route for each individual container (i.e. assign the container to a block to be stored) based on two competing objectives: (1) balance the workload among yard blocks, and (2) minimize the distance traveled by internal trucks between yard blocks and berths. The model utilizes an ant-based control method. It exploits the trail laying behavior of ant colonies where ants deposit pheromones as a function of traveled distance and congestion at the blocks. The route of a container (i.e. selection of a yard block) is based on the pheromone distribution on the network. The results from experiments show that the proposed approach is effective in balancing the workload among yard blocks and reducing the distance traveled by internal transport vehicles during vessel loading and unloading operations.

Reducing Truck Turn Times at Marine Terminals with Appointment Scheduling

This paper addresses a critical component of truck appointment systems: scheduling rules. The goal of this study is to gain an understanding of how the various scheduling rules affect resource utilization and truck turn time in grounded operations. Such an understanding could influence terminal operators and appointment service providers to make changes to their current scheduling practice. To this end, this study seeks to develop a framework for the evaluation of (a) the performance of various simple appointment-scheduling rules under a variety of operating scenarios and (b) the major factors affecting the performance of scheduling rules. This study considers two types of appointment-scheduling strategies that were adopted from the health care sector: (a) individual appointment systems (IASs) and (b) block appointment systems. To determine the effectiveness of the scheduling strategy, this study relies on a simulation model of a container terminal. Simulation is used because it provides a more realistic representation of the complex operations at terminals. In addition, it circumvents the restrictive assumptions of analytical methods. The simulation model developed was constructed with the Flexsim CT discrete event simulation software, the first commercially available off-the-shelf simulation tool for container terminals. The experimental results show a clear benefit for a terminal without an appointment system to use the IAS. Such a scheduling system keeps the yard cranes highly utilized, and it improves the internal yard turn time by about 44%. With the proper spacing between appointments, the IAS can be effective even when a good portion of trucks are walk-ins, no-shows, or late (up to 1 h).

Improving efficiency of drayage operations at seaport container terminals through the use of an appointment system

Designs of seaport container terminals involve three major infrastructure components: berth, container yard, and gate. In addition, Information Technology (e.g. terminal operations system, gate automation, and wireless handhelds) is becoming an integral component of container terminals. Beyond these traditional components, an emerging and potentially effective strategy, terminal planners need to consider to improve gate throughput, is the appointment system. Not only the use of an appointment system by a terminal can facilitate the movement of trucks in and out of the terminal, it can also help the terminal to manage its labor and yard resources. There are challenges to designing an effective appointment system. In this paper, two aspects of the appointment system are examined to provide insight to terminal planners. One parameter of an appointment system is the cap (i.e. limit) on the number of trucks that can enter a zone in the yard per time window. Limiting truck arrivals can be beneficial to some extent; however, if the caps are not set properly, it could be detrimental to both the terminal and truckers. The effect of limiting truck arrivals on crane utilization will be explored in this paper. A second aspect of the appointment system that will be examined in this paper is the scheduling rules (individual appointment system versus block appointment system) and their effects on resource utilization and truck turn time in grounded operations.

Modeling interruptions and patient flow in a preoperative hospital environment

Late starting surgeries at a Greenville Memorial Hospital have been shown to cause process and scheduling disruptions, and are a major contributor to dissatisfaction among patients and hospital staff. The preoperative system requires the preparation of a high volume of patients, each with an individual set of characteristics and array of required tasks before surgery. Staff resources do not have a prescribed sequence of activities nor mutually exclusive duties. A novel discrete event modeling paradigm has been adopted for simulating the complex behavior of the preoperative system, identifying the underlying causes of process inefficiencies, and testing mitigating strategies. Current investigations are underway to shift the prescriptive approach of resource decision-making towards an agent-based approach, allowing resources to select their workload in such a way that achieves maximum utility for the agent.

Mining the Sources of Delay for Dray Trucks at Container Terminals

To isolate the causes of abnormally high truck turn time, this paper develops a methodology for examining the sources of delay for dray trucks at container terminals. It is motivated by the need of port authorities and terminal operators to develop specialized solutions to reduce turn time based on terminal-specific causes. Although many ports have taken steps to improve the general level of service for trucks, such as establishing chassis pools and extending gate hours, fewer have performed the transaction-level analysis required to determine why a certain subset of operations is significantly higher than the average, thereby hindering the overall level of service. After problematic steps in the truck transaction process are isolated, terminals can select and deploy a range of technological or organizational countermeasures to address the problem. This study draws on a database of truck activity from the port of Houston, Texas. Because of the large number of gate transactions and potential factors that could contribute to high truck turn time, a data mining technique is used. Specifically, a decision tree technique is explored and described in this paper. Results indicate that import transactions that require chassis tend to have high truck turn time because truckers need to find a matching chassis. This paper demonstrates how decision trees can be used by port authorities and terminal operators to gain insight into their operations without the need to perform exhaustive data analysis.

Freight Traffic Assignment Methodology for Large-Scale Road–Rail Intermodal Networks

A methodology is proposed for freight traffic assignment in large-scale road–rail intermodal networks. To obtain the user–equilibrium freight flows, a path-based assignment algorithm (gradient projection) was proposed. The developed methodology was tested on the U.S. intermodal network by using the 2007 freight demand for truck, rail, and road–rail intermodal from the Freight Analysis Framework, Version 3 (FAF3). The results indicate that the proposed methodologys projected flow pattern is similar to the FAF3 assignment. The proposed methodology can be used by transportation planners and decision makers to forecast freight flows and to evaluate strategic network expansion options.

Estimating Truck Queuing Time at Marine Terminal Gates

Truck queuing at marine terminal gates has long been recognized as a source of emissions problems because of the many trucks that are idling. For this reason, stakeholders have a great interest in lessening the severity of the problem. To assist these stakeholders in addressing the congestion problem, baseline data and predictive models are needed. Unfortunately, data on truck queuing and research on the methodologies that can be used to estimate truck queuing time are limited. With an increasing number of marine terminals offering live webcam views of their gates to manage demand for the terminals, these webcams could be used to gather much-needed truck queuing information and other truck-related data. Data collected from the webcams were used to develop models to predict truck queuing times on an hourly or daily basis. Given the inherent fuzziness of the truck arrival data, this study evaluated the suitability of four predictive models capable of dealing with fuzzy data: multiple linear regression, fuzzy regression, clustering fuzzy regression, and support vector machines. Analysis showed that fuzzy regression outperformed other methods for the given data set.

Evaluation of Medication Administration Process: Tools and Techniques

Health care safety improvement focuses on redesign of high-risk health care processes such as the medication administration process (MAP) to enhance safety and reduce errors. A key limitation of MAP redesign efforts is the lack of validated tools by which to accurately record process observations. This paper discusses a pilot study conducted to develop and evaluate a handheld device application for recording observations of oral MAP functions and tasks. The aim of the study was to leverage existing technology to develop an observation recording device comparable to handwritten recordings commonly used to document workflow observations in health care settings. Device recordings were statistically compared to handwritten recordings of the same MAP functions and tasks. Findings provided preliminary evidence that handheld device recordings were consistent with handwritten recordings for documenting task duration but not task sequence. Interruptions were not examined due to insufficient data and additional research is needed.