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Articles 1 - 30 of 120
Full-Text Articles in Engineering
Tracked Vehicle Physics-Based Energy Modelling And Series Hybrid System Optimisation For The Bradley Fighting Vehicle, Travis E. Mcwhirter, Torrey J. Wagner, John E. Stubbs, Denise M. Rizzo, Jada B. Williams
Tracked Vehicle Physics-Based Energy Modelling And Series Hybrid System Optimisation For The Bradley Fighting Vehicle, Travis E. Mcwhirter, Torrey J. Wagner, John E. Stubbs, Denise M. Rizzo, Jada B. Williams
Faculty Publications
A hybrid electric tracked ground vehicle (HETGV) can reduce military fuel usage, however a review of current tools determined they are not suitable to estimate HEGTV performance. Based on topographic data and vehicle attributes, this research developed an estimation tool by creating a model to determine tracked vehicle energy and fuel requirements, and using these requirements, created a HEGTV cost and performance optimisation for the Bradley fighting vehicle energy system. The optimised design reduced fuel consumption by 15%, and met the vehicle's peak power requirement of 365 kW, with a recommended configuration of a 135 kW generator and 100 kWh …
Investigation Of Retrieved Cardiac Devices, Anmar Salih, Iosif Papadakis Ktistakis, Spyridon Manganas, Abdul Wase, Tarun Goswami
Investigation Of Retrieved Cardiac Devices, Anmar Salih, Iosif Papadakis Ktistakis, Spyridon Manganas, Abdul Wase, Tarun Goswami
Biomedical, Industrial & Human Factors Engineering Faculty Publications
Damage assessment of lead and pulse generator with various exposure times is important in the development of cardiac devices. Approximately, 92.1 million patients in the US suffer from cardiovascular diseases with an estimated healthcare cost of over $300 billion and at least one million with implantable cardiac devices. These devices are complex and composed on multiple levels and present challenges while assessing the damage. However, the study on the analysis of cardiac devices may lend insight into common damage patterns and improve future cardiac devices design. The objective of this work is to perform a thorough in vivo damage assessment …
Investigation Of A Neuro-Stimulator Retrieved Posthumously, Megan Markl, Rodney J. Gutherie, Tarun Goswami
Investigation Of A Neuro-Stimulator Retrieved Posthumously, Megan Markl, Rodney J. Gutherie, Tarun Goswami
Biomedical, Industrial & Human Factors Engineering Faculty Publications
A neurostimulator was investigated in this paper posthumously. Device was presented to our anatomical gift program. Investigation was multi-fold and contained visual inspection, using an optical microscope, and mechanical and electrical testing of leads and its insulator. It was concluded that the device could have been damaged during implantation, in vivo, during removal, and/or during transportation to author’s laboratories. The damage observed on the lead insulation is similar to that which can occur due to anchoring of the lead and hardening due to oxidation. Insulation stiffness was determined to be 1/10 of new insulator. The results reported here on the …
Simulation Of Skull Fracture Due To Falls, Anthony Vicini, Tarun Goswami
Simulation Of Skull Fracture Due To Falls, Anthony Vicini, Tarun Goswami
Biomedical, Industrial & Human Factors Engineering Faculty Publications
This study presents novel predictive equations for von Mises stress values of bones in the frontal and lateral regions of the skull. The equations were developed based on results of a finite element model developed during this research. The model was validated for frontal and lateral loading conditions with input values mimetic to fall scenarios. Using neural network processing of the information derived from the model achieved R2 values of 0.9990 for both the stress and deflection. Based on the outcome of the fall victims, a threshold von Mises stress of 40.9 to 46.6 MPa was found to indicate skull …
A Mathematical Programming Model For The Green Mixed Fleet Vehicle Routing Problem With Realistic Energy Consumption And Partial Recharges, Vincent F. Yu, Panca Jodiwan, Aldy Gunawan, Audrey Tedja Widjaja
A Mathematical Programming Model For The Green Mixed Fleet Vehicle Routing Problem With Realistic Energy Consumption And Partial Recharges, Vincent F. Yu, Panca Jodiwan, Aldy Gunawan, Audrey Tedja Widjaja
Research Collection School Of Computing and Information Systems
A green mixed fleet vehicle routing with realistic energy consumption and partial recharges problem (GMFVRP-REC-PR) is addressed in this paper. This problem involves a fixed number of electric vehicles and internal combustion vehicles to serve a set of customers. The realistic energy consumption which depends on several variables is utilized to calculate the electricity consumption of an electric vehicle and fuel consumption of an internal combustion vehicle. Partial recharging policy is included into the problem to represent the real life scenario. The objective of this problem is to minimize the total travelled distance and the total emission produced by internal …
Hedge Fund Replication Using Strategy Specific Factors, Sujit Subhash, David Lee Enke
Hedge Fund Replication Using Strategy Specific Factors, Sujit Subhash, David Lee Enke
Engineering Management and Systems Engineering Faculty Research & Creative Works
Hedge funds have traditionally served wealthy individuals and institutional investors with the promise of delivering protection of capital and uncorrelated positive returns irrespective of market direction, allowing them to better manage portfolio risk. However, the financial crisis of 2008 has heightened investor sensitivity to the high fees, illiquidity, lack of transparency, and lockup periods typically associated with hedge funds. Hedge fund replication products, or clones, seek to answer these challenges by providing daily liquidity, transparency, and immediate exposure to a desired hedge fund strategy. Nonetheless, although lowering cost and adding simplicity by using a common set of factors, traditional replication …
Predicting The Daily Return Direction Of The Stock Market Using Hybrid Machine Learning Algorithms, X. Zhong, David Lee Enke
Predicting The Daily Return Direction Of The Stock Market Using Hybrid Machine Learning Algorithms, X. Zhong, David Lee Enke
Engineering Management and Systems Engineering Faculty Research & Creative Works
Big data analytic techniques associated with machine learning algorithms are playing an increasingly important role in various application fields, including stock market investment. However, few studies have focused on forecasting daily stock market returns, especially when using powerful machine learning techniques, such as deep neural networks (DNNs), to perform the analyses. DNNs employ various deep learning algorithms based on the combination of network structure, activation function, and model parameters, with their performance depending on the format of the data representation. This paper presents a comprehensive big data analytics process to predict the daily return direction of the SPDR S&P 500 …
An Agent Based Model Of Passenger Boarding For Examining Commercial Aircraft Boarding Strategies, Frank W. Ciarallo, Raymond R. Hill, Kerry K. Ward
An Agent Based Model Of Passenger Boarding For Examining Commercial Aircraft Boarding Strategies, Frank W. Ciarallo, Raymond R. Hill, Kerry K. Ward
Faculty Publications
We use an agent-based simulation methodology to study airline passenger boarding using measures that reflect both the customer experience and airline efficiency perspective. This approach supports exploration of models of actual aircraft used in practice and detailed modeling of passenger dynamics. This paper discusses the modeling approach and a set of experiments comparing several boarding strategies from practical settings as well as the literature.
A Governance Perspective For System-Of-Systems, Polinpapilinho F. Katina, Charles B. Keating, James A. Bobo, Tyrone S. Toland
A Governance Perspective For System-Of-Systems, Polinpapilinho F. Katina, Charles B. Keating, James A. Bobo, Tyrone S. Toland
Engineering Management & Systems Engineering Faculty Publications
The operating landscape of 21st century systems is characteristically ambiguous, emergent, and uncertain. These characteristics affect the capacity and performance of engineered systems/enterprises. In response, there are increasing calls for multidisciplinary approaches capable of confronting increasingly ambiguous, emergent, and uncertain systems. System of Systems Engineering (SoSE) is an example of such an approach. A key aspect of SoSE is the coordination and the integration of systems to enable ‘system-of-systems’ capabilities greater than the sum of the capabilities of the constituent systems. However, there is a lack of qualitative studies exploring how coordination and integration are achieved. The objective of this …
Better Beware: Comparing Metacognition For Phishing And Legitimate Emails, Casey I. Canfield, Baruch Fischhoff, Alex Davis
Better Beware: Comparing Metacognition For Phishing And Legitimate Emails, Casey I. Canfield, Baruch Fischhoff, Alex Davis
Engineering Management and Systems Engineering Faculty Research & Creative Works
Every electronic message poses some threat of being a phishing attack. If recipients underestimate that threat, they expose themselves, and those connected to them, to identity theft, ransom, malware, or worse. If recipients overestimate that threat, then they incur needless costs, perhaps reducing their willingness and ability to respond over time. In two experiments, we examined the appropriateness of individuals' confidence in their judgments of whether email messages were legitimate or phishing, using calibration and resolution as metacognition metrics. Both experiments found that participants had reasonable calibration but poor resolution, reflecting a weak correlation between their confidence and knowledge. These …
Correction To: Better Beware: Comparing Metacognition For Phishing And Legitimate Emails (Metacognition And Learning, (2019), 14, 3, (343-362), 10.1007/S11409-019-09197-5), Casey I. Canfield, Baruch Fischhoff, Alex Davis
Correction To: Better Beware: Comparing Metacognition For Phishing And Legitimate Emails (Metacognition And Learning, (2019), 14, 3, (343-362), 10.1007/S11409-019-09197-5), Casey I. Canfield, Baruch Fischhoff, Alex Davis
Engineering Management and Systems Engineering Faculty Research & Creative Works
The article "Better beware: comparing metacognition for phishing and legitimate emails", written by Casey Inez Canfield, Baruch Fischhoff and Alex Davis, was originally published electronically on the publisher's internet portal (currently SpringerLink) on 20 July 2019 without open access.
Deep Brain Stimulation: Prediction Model For Volume Of Tissue Stimulated, Melissa Jones, Tarun Goswami
Deep Brain Stimulation: Prediction Model For Volume Of Tissue Stimulated, Melissa Jones, Tarun Goswami
Biomedical, Industrial & Human Factors Engineering Faculty Publications
An attempt has been made to understand deep brain stimulation in humans via marketable devices that are approved by the US Food and Drug Administration. The electrode characteristics were presented to influence the volume of tissue stimulated. Experimental data were digitized and VTS data were presented a function of electrode diameter, aspect ratio, applied current, pulse duration, voltage and frequency. Amongst other trends voltage and VTS were found to exhibit a three-stage relation, where Stage II characteristics were represented by a linear equation. It is in this stage, the VTS was found to be stable and where the most effective …
Dual Degree Agreement For College Of Engineering With Tennessee Wesleyan, University Of Tennessee, Knoxville
Dual Degree Agreement For College Of Engineering With Tennessee Wesleyan, University Of Tennessee, Knoxville
SACSCOC Documentation
No abstract provided.
Conditional Survival Analysis For Concrete Bridge Decks, Azam Nabizadeh, Habib Tabatabai, Mohammad A. Tabatabai
Conditional Survival Analysis For Concrete Bridge Decks, Azam Nabizadeh, Habib Tabatabai, Mohammad A. Tabatabai
Civil and Environmental Engineering Faculty Articles
Bridge decks are a significant factor in the deterioration of bridges, and substantially affect long-term bridge maintenance decisions. In this study, conditional survival (reliability) analysis techniques are applied to bridge decks to evaluate the age at the end of service life using the National Bridge Inventory records. As bridge decks age, the probability of survival and the expected service life would change. The additional knowledge gained from the fact that a bridge deck has already survived a specific number of years alters (increases) the original probability of survival at subsequent years based on the conditional probability theory. The conditional expected …
A Transdisciplinary Collaboration And Innovation Education Model And Experience, Brian Laduca, Michelle Hayford, Adrienne Ausdenmoore, Jerome Yorke, Kevin Hallinan, Rebecca Blust, Anne R. Crecelius, Philip Appiah-Kubi, Jennifer Katz-Buonconintro, Jana Bennett, Jackie Marshall Arnold, Connie L. Bowman, Castel Sweet
A Transdisciplinary Collaboration And Innovation Education Model And Experience, Brian Laduca, Michelle Hayford, Adrienne Ausdenmoore, Jerome Yorke, Kevin Hallinan, Rebecca Blust, Anne R. Crecelius, Philip Appiah-Kubi, Jennifer Katz-Buonconintro, Jana Bennett, Jackie Marshall Arnold, Connie L. Bowman, Castel Sweet
Engineering Management and Systems Faculty Publications
As the interconnectedness of the world grows, the need to prepare college students capable of addressing complexity likewise grows. In this context, the University of Dayton has developed and tested a transdisciplinary model for education. This model links multiple classes from different disciplines via a common theme and within a common space. It also employs an educational model premised on the following trajectory: disciplinary content development / transdisciplinary observation (empathy); transdisciplinary disruption leading to “A-Ha” observations which transform the disciplinary directions; and lastly transdisciplinary informed design and research. Central to this model is a 3,500 square foot common space used …
The Business Case For Industrial Safety: Revealing The Comprehensive Value Of Ergonomic Investments For Manufacturing Enterprises In Industry 4.0, Shane Stan
Honors Theses
How can today’s manufacturing enterprises construct, implement, and optimize modern safety initiatives in a manner that will present maximum return on investment and facilitate enterprise growth? Furthermore, how can these manufacturers assure individual ergonomic investments become part of a larger strategy to facilitate organizational change in safety? This work addresses these questions by placing industrial ergonomics in a business improvement context which comprehensively presents the financial returns and growth opportunities poised by modern safety initiatives. Additionally, to further strengthen the business case for industrial safety, an ergonomic action planning framework is established to guide the creation of holistic safety programs …
A Mixed Method Study Of Infrastructure Resilience Education And Instruction, John Richards, Suzanna Long
A Mixed Method Study Of Infrastructure Resilience Education And Instruction, John Richards, Suzanna Long
Engineering Management and Systems Engineering Faculty Research & Creative Works
As the frequency and severity of natural and man-made disasters increases, the importance of improving the resilience of complex infrastructure systems in an uncertain environment is increasingly critical. Proper training and education are key components to addressing this issue, but it is unclear how and where modeling under uncertainty, infrastructure systems management, and resilient systems are integrated into the standard undergraduate and graduate engineering management curriculum. This research uses a mixed method to determine whether and at what level engineering managers receive instruction regarding the implementation of tools and techniques to improve infrastructure resilience. A review of current courses and …
Flood Management Deep Learning Model Inputs: A Review Of Necessary Data And Predictive Tools, Jacob Hale, Suzanna Long, Steven Corns, Tom Shoberg
Flood Management Deep Learning Model Inputs: A Review Of Necessary Data And Predictive Tools, Jacob Hale, Suzanna Long, Steven Corns, Tom Shoberg
Engineering Management and Systems Engineering Faculty Research & Creative Works
Current flood management models are often hampered by the lack of robust predictive analytics, as well as incomplete datasets for river basins prone to heavy flooding. This research uses a State-of-the-Art matrix (SAM) analysis and integrative literature review to categorize existing models by method and scope, then determines opportunities for integrating deep learning techniques to expand predictive capability. Trends in the SAM analysis are then used to determine geospatial characteristics of the region that can contribute to flash flood scenarios, as well as develop inputs for future modeling efforts. Preliminary progress on the selection of one urban and one rural …
Risk Awareness Enhancement Systems For Hazmat Transportation: Prototyping And Technology Evaluation, Jian Xue, Katherine Linville, Yu Li, Pranav Nitin Godse, Suzanna Long, Ruwen Qin
Risk Awareness Enhancement Systems For Hazmat Transportation: Prototyping And Technology Evaluation, Jian Xue, Katherine Linville, Yu Li, Pranav Nitin Godse, Suzanna Long, Ruwen Qin
Engineering Management and Systems Engineering Faculty Research & Creative Works
Workers of hazardous material (hazmat) transportation have a higher chance than other workers to be exposed to various risks in their workplace. Assisting them to safely operate in their workplace in a near real-time manner is in particular need. This paper presents a study of designing, prototyping and developing feedback systems to help increase the risk awareness of workers in the loading and uploading phases of hazmat transportation. The first system was prototyped on an Arduino board, serving as the reference for system development. Then, the second system, named a Bluetooth Low Energy (BLE) beacon based system, was designed as …
Opportunities And Challenges For Rural Broadband Infrastructure Investment, Casey I. Canfield, Ona Egbue, Jacob Hale, Suzanna Long
Opportunities And Challenges For Rural Broadband Infrastructure Investment, Casey I. Canfield, Ona Egbue, Jacob Hale, Suzanna Long
Engineering Management and Systems Engineering Faculty Research & Creative Works
Insufficient internet access is holding back local economies, reducing educational outcomes, and creating health disparities in rural areas of the U.S. At present, federal and state funding is available for rural broadband infrastructure deployment, but existing efforts have not invested in analytical work to maximize efficiency and minimize cost. In this study, we use a state-of-the-art matrix (SAM) to identify key challenges and opportunities facing rural broadband infrastructure from previous research and government reports. We focus on six themes: (1) technology, (2) hardware costs, (3) financing, (4) adoption, (5) regulatory/legal, and (6) management. We highlight key issues to be addressed …
Data-Driven Predictive Maintenance Scheduling Policies For Railways, Pedro Cesar Lopes Gerum, Ayca Altay, Melike Baykal-Gürsoy
Data-Driven Predictive Maintenance Scheduling Policies For Railways, Pedro Cesar Lopes Gerum, Ayca Altay, Melike Baykal-Gürsoy
Supply Chain Management
Inspection and maintenance activities are essential to preserving safety and cost-effectiveness in railways. However, the stochastic nature of railway defect occurrence is usually ignored in literature; instead, defect stochasticity is considered independently of maintenance scheduling. This study presents a new approach to predict rail and geometry defects that relies on easy-to-obtain data and integrates prediction with inspection and maintenance scheduling activities. In the proposed approach, a novel use of risk-averse and hybrid prediction methodology controls the underestimation of defects. Then, a discounted Markov decision process model utilizes these predictions to determine optimal inspection and maintenance scheduling policies. Furthermore, in the …
Paints-R-Us Term Project, Tyler Campbell, Skye Gilbreth, Michael Oluwole, Elijah Raffo, Brad Unruh
Paints-R-Us Term Project, Tyler Campbell, Skye Gilbreth, Michael Oluwole, Elijah Raffo, Brad Unruh
Engineering and Technology Management Student Projects
This project will consider a linear product mix optimization problem for a fictional paint company, Paints-R-Us. Paints-R-Us is a wholesale paint manufacturer located in the Pacific Northwest. The Global Production Manager, Steve Brush, has been tasked with maximizing Paints-R-Us’s profit in the upcoming quarter. Steve Brush oversees the global production plan, and in collaboration with the production planners will develop a production plan which optimizes the profits that Paints-R-Us can create in the quarter accounting for the following criteria:
• Demand in the given quarter for each of the 5 paint types that Paints-R-Us produces • The warehousing storage capacity …
Insulation Sensitivity Analysis For An Optimized Fabric Shelter Off-Grid Hybrid Energy System, Jay F. Pearson [*], Torrey J. Wagner, Steven Schuldt
Insulation Sensitivity Analysis For An Optimized Fabric Shelter Off-Grid Hybrid Energy System, Jay F. Pearson [*], Torrey J. Wagner, Steven Schuldt
Faculty Publications
During military and disaster relief operations, connecting to an established electrical grid is rarely an option. In these situations, camps consisting of poorly insulated fabric shelters are predominantly powered by inefficient diesel generators that require frequent fuel resupply. In order to reduce the fuel demand of these generators, camps may utilize photovoltaic-battery systems. This paper presents an innovative cost-performance model capable of optimizing solar array size, battery backup system, and shelter insulation type to minimize the operating cost of powering a single fabric shelter. Model performance was evaluated using one year of insolation, weather and energy requirement data from a …
The Impact Of Executing A Warehouse Management System Change: A Case Study, Nicholas J. Cross
The Impact Of Executing A Warehouse Management System Change: A Case Study, Nicholas J. Cross
Masters Theses & Specialist Projects
The increased demand on distribution centers to provide quicker turnarounds from receiving to shipping while maintaining precise inventory accuracies is spurring the acquisition of a warehouse management system (WMS) to improve operations and increase efficiency. With the rapid expansion of WMS technology, it seems inevitable that warehouses will outgrow inefficient operational processes and switch to a system that can accommodate rapid development. Research has explained the financial burdens and benefits of acquiring a WMS, but there’s been minimal research describing the impacts of the actual implementation. This study took place within a 600,000 sq. ft. fulfillment center and focused on …
An Empirical Study Of Mixed Integer Programming Formulations Of The Backhaul Profit Maximization Problem, Yulan Bai, Eli V. Olinick
An Empirical Study Of Mixed Integer Programming Formulations Of The Backhaul Profit Maximization Problem, Yulan Bai, Eli V. Olinick
Operations Research and Engineering Management
Solving an instance of the Backhaul Profit Maximization Problem (BPMP) requires simultaneously solving two problems: (1) determining how to route an empty delivery vehicle back from its current location to its depot by a scheduled arrival time, and (2) selecting a profit-maximizing subset of delivery requests between various locations on the route subject to the vehicle's capacity. We propose and test a series of enhancements to the node-arc and triples mixed integer programming formulations of BPMP found in the literature and develop a multi-criteria Composite Index Method (CIM) to evaluate the results. We find that CPLEX takes 5 to 34 …
Design And Validation Of A Modular Instrument To Measure Torque And Energy Consumption In Industrial Operations, Mary De La Cruz, Ramiro Gonzalez, Jesus A. Gomez, Atilano Mendoza, Javier A. Ortega
Design And Validation Of A Modular Instrument To Measure Torque And Energy Consumption In Industrial Operations, Mary De La Cruz, Ramiro Gonzalez, Jesus A. Gomez, Atilano Mendoza, Javier A. Ortega
Mechanical Engineering Faculty Publications and Presentations
A modular torque measuring instrument capable of performing tapping torque tests (TTT) according to the ASTM D-5619 standard was designed, developed, and validated. With this new instrument, the performance of different lubricants can be evaluated in terms of frictional torque and energy consumption during tapping processes. This instrument can adapt onto any conventional milling machine or CNC machine and operate under various machining operations such as tapping, drilling, and other processes. To validate the design and performance of this new device, three commercially available lubricants were evaluated. From the three tested conditions, the results showed good repeatability, with consistent results …
Kidney-Related Operations Research: A Review, Mahdi Fathi, Marzieh Khakifirooz
Kidney-Related Operations Research: A Review, Mahdi Fathi, Marzieh Khakifirooz
Bagley College of Engineering Publications and Scholarship
Operations research and optimization in healthcare and disease modeling have received significant attention in the last three decades. This article surveys several perspectives of operations research techniques in kidney disease, such as graph theory, queueing theory, Markov chain, and phase-type distribution (PTD). The kidney-related problems include kidney exchange problem, the modeling of kidney disease progression, kidney transplantation, and the complex relationship between chronic kidney disease (gradual loss of kidney function over time) and acute kidney injury (sudden episode of kidney failure in a few hours or a few days). Each section is summarized by some discussion regarding the limitation of …
Improving Law Enforcement Daily Deployment Through Machine Learning-Informed Optimization Under Uncertainty, Jonathan David Chase, Duc Thien Nguyen, Haiyang Sun, Hoong Chuin Lau
Improving Law Enforcement Daily Deployment Through Machine Learning-Informed Optimization Under Uncertainty, Jonathan David Chase, Duc Thien Nguyen, Haiyang Sun, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Urban law enforcement agencies are under great pressure to respond to emergency incidents effectively while operating within restricted budgets. Minutes saved on emergency response times can save lives and catch criminals, and a responsive police force can deter crime and bring peace of mind to citizens. To efficiently minimize the response times of a law enforcement agency operating in a dense urban environment with limited manpower, we consider in this paper the problem of optimizing the spatial and temporal deployment of law enforcement agents to predefined patrol regions in a real-world scenario informed by machine learning. To this end, we …
Data-Driven Surgical Duration Prediction Model For Surgery Scheduling: A Case-Study For A Practice-Feasible Model In A Public Hospital, Kar Way Tan, Francis Ngoc Hoang Long Nguyen, Boon Yew Ang, Jerald Gan, Sean Shao Wei Lam
Data-Driven Surgical Duration Prediction Model For Surgery Scheduling: A Case-Study For A Practice-Feasible Model In A Public Hospital, Kar Way Tan, Francis Ngoc Hoang Long Nguyen, Boon Yew Ang, Jerald Gan, Sean Shao Wei Lam
Research Collection School Of Computing and Information Systems
Hospitals have been trying to improve the utilization of operating rooms as it affects patient satisfaction, surgery throughput, revenues and costs. Surgical prediction model which uses post-surgery data often requires high-dimensional data and contains key predictors such as surgical team factors which may not be available during the surgical listing process. Our study considers a two-step data-mining model which provides a practical, feasible and parsimonious surgical duration prediction. Our model first leverages on domain knowledge to provide estimate of the first surgeon rank (a key predicting attribute) which is unavailable during the listing process, then uses this predicted attribute and …
Decision Making For Improving Maritime Traffic Safety Using Constraint Programming, Saumya Bhatnagar, Akshat Kumar, Hoong Chuin Lau
Decision Making For Improving Maritime Traffic Safety Using Constraint Programming, Saumya Bhatnagar, Akshat Kumar, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Maritime navigational safety is of utmost importance to prevent vessel collisions in heavily trafficked ports, and avoid environmental costs. In case of a likely near miss among vessels, port traffic controllers provide assistance for safely navigating the waters, often at very short lead times. A better strategy is to avoid such situations from even happening. To achieve this, we a) formalize the decision model for traffic hotspot mitigation including realistic maritime navigational features and constraints through consultations with domain experts; and b) develop a constraint programming based scheduling approach to mitigate hotspots. We model the problem as a variant of …