Operations Research, Systems Engineering and Industrial Engineering Commons^™

System-Wide Prediction Of General, All-Cause, Preventable Hospital Readmissions, Ken Musselman, Brandon Pope, Steve Witz, Zhiyi Tian, Lingsong Zhang, Linda Leon, Ann Davis

RCHE Publications

Existing studies of hospital readmissions typically focus on specific diagnoses, age groups, discharge dispositions, payer classes, or hospitals, and often use small samples. It is not clear how predictive models generated from such studies generalize across diseases, hospitals, or time periods. In this study, a logistic regression model of readmission risk within 30 days based on hospital administrative data was constructed and validated across hospitals and time periods. The hospitals included both general and specialty hospitals such as long-term care, women’s, and children’s hospitals. The administrative data included information on patient’s demographics, diagnoses, procedures, and discharge disposition. Derivation and validation …

Pre-Mission Input Requirements To Enable Successful Sample Collection By A Remote Field/Eva Team, Barbara A. Cohen, Darlene S. S. Lim, Kelsey E. Young, Anna Brunner, Richard C. Elphic, Audrey Horne, Mary C. Kerrigan, Gordon O. Osinski, John R. Skok, Steven W. Squyres, David Saint-Jacques, Jennifer L. Heldmann

Journal of Human Performance in Extreme Environments

We used a field excursion to the West Clearwater Lake Impact structure as an opportunity to test factors that contribute to the decisions a remote field team (for example, astronauts conducting extravehicular activities (EVA) on planetary surfaces) makes while collecting samples for return to Earth. We found that detailed background on the analytical purpose of the samples, provided to the field team, enables them to identify and collect samples that meet specific analytical objectives. However, such samples are not always identifiable during field reconnaissance activities, and may only be recognized after outcrop characterization and interpretation by crew and/or science team …

Developing And Testing An Anguilliform Robot Swimming With Theoretically High Hydrodynamic Efficiency, John B. Potts Iii

University of New Orleans Theses and Dissertations

An anguilliform swimming robot replicating an idealized motion is a complex marine vehicle necessitating both a theoretical and experimental analysis to completely understand its propulsion characteristics. The ideal anguilliform motion within is theorized to produce ``wakeless'' swimming (Vorus, 2011), a reactive swimming technique that produces thrust by accelerations of the added mass in the vicinity of the body. The net circulation for the unsteady motion is theorized to be eliminated.

The robot was designed to replicate the desired, theoretical motion by applying control theory methods. Independent joint control was used due to hardware limitations. The fluid velocity vectors in the …

Robust Distributed Scheduling Via Time Period Aggregation, Shih-Fen Cheng, John Tajan, Hoong Chuin Lau

Shih-Fen Cheng

In this paper, we evaluate whether the robustness of a market mechanism that allocates complementary resources could be improved through the aggregation of time periods in which resources are consumed. In particular, we study a multi-round combinatorial auction that is built on a general equilibrium framework. We adopt the general equilibrium framework and the particular combinatorial auction design from the literature, and we investigate the benefits and the limitation of time-period aggregation when demand-side uncertainties are introduced. By using simulation experiments on a real-life resource allocation problem from a container port, we show that, under stochastic conditions, the performance variation …

Robust Distributed Scheduling Via Time Period Aggregation, Shih-Fen Cheng, John Tajan, Hoong Chuin Lau

Shih-Fen Cheng

In this paper, we evaluate whether the robustness of a market mechanism that allocates complementary resources could be improved through the aggregation of time periods in which resources are consumed. In particular, we study a multi-round combinatorial auction that is built on a general equilibrium framework. We adopt the general equilibrium framework and the particular combinatorial auction design from the literature, and we investigate the benefits and the limitation of time-period aggregation when demand-side uncertainties are introduced. By using simulation experiments on a real-life resource allocation problem from a container port, we show that, under stochastic conditions, the performance variation …

Robust Distributed Scheduling Via Time Period Aggregation, Shih-Fen Cheng, John Tajan, Hoong Chuin Lau

Shih-Fen CHENG

In this paper, we evaluate whether the robustness of a market mechanism that allocates complementary resources could be improved through the aggregation of time periods in which resources are consumed. In particular, we study a multi-round combinatorial auction that is built on a general equilibrium framework. We adopt the general equilibrium framework and the particular combinatorial auction design from the literature, and we investigate the benefits and the limitation of time-period aggregation when demand-side uncertainties are introduced. By using simulation experiments on a real-life resource allocation problem from a container port, we show that, under stochastic conditions, the performance variation …

Warranty Period And Product Price Optimization For Remanufactured Products, Yuxi Liu

Theses and Dissertations

This study considers a remanufactured electrical product under a tiered warranty policy. Warranty is key in ensuring a good manufacturer—consumer relationship. Manufacturers hope to minimize warranty costs while consumers believe that good warranty promises better product quality and reliability. This Thesis presents an optimal warranty period from the perspective of a manufacturer to maximize the total expected profits, while ensuring sustained consumer relation. We use real data from a local company with a global supply chain to provide a numerical example.

Robust Execution Strategies For Project Scheduling With Unreliable Resources And Stochastic Durations, Na Fu, Hoong Chuin Lau, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

The resource-constrained project scheduling problem with minimum and maximum time lags (RCPSP/max) is a general model for resource scheduling in many real-world problems (such as manufacturing and construction engineering). We consider RCPSP/max problems where the durations of activities are stochastic and resources can have unforeseen breakdowns. Given a level of allowable risk, (Formula presented.), our mechanisms aim to compute the minimum robust makespan execution strategy. Robust makespan for an execution strategy is any makespan value that has a risk less than (Formula presented.). The risk for a makespan value, (Formula presented.) given an execution strategy, is the probability that a …

A Systems Approach To Point Source Indication Of Metformin Found In Local Water Systems – The Case Of Milwaukee County, Mohamed Salem Baitelmal

Theses and Dissertations

Pharmaceutical pollutants are present in traceable concentrations in Milwaukee County water system and Lake Michigan. The actual point sources and nature of entry into the water system is difficult to determine with certainty. Pharmaceuticals have been found to persist at the South Shore Wastewater Treatment Facility (SSWTF) in Milwaukee, Wisconsin. The highest concentration was found to be for the pharmaceutical drug metformin. Metformin is a first line drug for the treatment of type 2 diabetes mellitus.

The broad goal of this exploratory study; the first of its kind, is to correlate trace concentrations of drugs to the point sources. Particularly, …

Water Withdrawal And Consumption Reduction Analysis For Electrical Energy Generation System, Narjes Nouri

Theses and Dissertations

There is an increasing concern over shrinking water resources. Water use in the energy sector primarily occurs in electricity generation. Anticipating scarcer supplies, the value of water is undoubtedly on the rise and design, implementation, and utilization of water saving mechanisms in energy generation systems are becoming inevitable. Most power plants generate power by boiling water to produce steam to spin electricity-generating turbines. Large quantities of water are often used to cool the steam in these plants. As a consequence, most fossil-based power plants in addition to consuming water, impact the water resources by raising the temperature of water withdrawn …

Spatiotemporal Sensing And Informatics For Complex Systems Monitoring, Fault Identification And Root Cause Diagnostics, Gang Liu

USF Tampa Graduate Theses and Dissertations

In order to cope with system complexity and dynamic environments, modern industries are investing in a variety of sensor networks and data acquisition systems to increase information visibility. Multi-sensor systems bring the proliferation of high-dimensional functional Big Data that capture rich information on the evolving dynamics of natural and engineered processes. With spatially and temporally dense data readily available, there is an urgent need to develop advanced methodologies and associated tools that will enable and assist (i) the handling of the big data communicated by the contemporary complex systems, (ii) the extraction and identification of pertinent knowledge about the environmental …

Designing Bus Transit Services For Routine Crowd Situations At Large Event Venues, Jianli Du, Shih-Fen Cheng, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

We are concerned with the routine crowd management problem after a major event at a known venue. Without properly design complementary transport services, such sudden crowd build-ups will overwhelm the existing infrastructure. In this paper, we introduce a novel flow-rate based model to model the dynamic movement of passengers over the transportation flow network. Based on this basic model, an integer linear programming model is proposed to solve the bus transit problem permanently. We validate our model against a real scenario in Singapore, where a newly constructed mega-stadium hosts various large events regularly. The results show that the proposed approach …

Developing An Optimal Model For Infant Home Visitation, Isaac Atuahene

Doctoral Dissertations

The United States, Great Britain, Denmark, Canada and many other countries have accepted home visitation (HV) as a promising strategy for interventions for infants after births and for their mothers. Prior HV studies have focused on theoretical foundations, evaluations of programs, cost/benefit analysis and cost estimation by using hospital/payer/insurance data to prove its effectiveness and high cost. As governments and private organizations continue to fund HVs, it is an opportune time to develop and formulate operations research (OR) models of HV coverage, quality and cost so they might be used in program implementation as done for adult home healthcare (HHC) …

Sails: Hybrid Algorithm For The Team Orienteering Problem With Time Windows, Aldy Gunawan, Hoong Chuin Lau, Kun Lu

Research Collection School Of Computing and Information Systems

The Team Orienteering Problem with Time Windows (TOPTW) is the extended version of the Orienteering Problem where each node is limited by a given time window. The objective is to maximize the total collected score from a certain number of paths. In this paper, a hybridization of Simulated Annealing and Iterated Local Search, namely SAILS, is proposed to solve the TOPTW. The efficacy of the proposed algorithm is tested using benchmark instances. The results show that the proposed algorithm is competitive with the state-of-the-art algorithms in the literature. SAILS is able to improve the best known solutions for 19 benchmark …

Ad-Hoc Automated Teller Machine Failure Forecast And Field Service Optimization, Michelle L. F. Cheong, Ping Shung Koo, B. Chandra Babu

Research Collection School Of Computing and Information Systems

As part of its overall effort to maintain good customer service while managing operational efficiency and reducing cost, a bank in Singapore has embarked on using data and decision analytics methodologies to perform better ad-hoc ATM failure forecasting and plan the field service engineers to repair the machines. We propose using a combined Data and Decision Analytics Framework which helps the analyst to first understand the business problem by collecting, preparing and exploring data to gain business insights, before proposing what objectives and solutions can and should be done to solve the problem. This paper reports the work in analyzing …

Modelling Supercomputer Maintenance Interrupts: Maintenance Policy Recommendations, Jagadish Cherukuri

Masters Theses

A supercomputer is a repairable system with large number of compute nodes interconnected to work in harmony to achieve superior computational performance. Reliability of such a complex system depends on an effective maintenance strategy that involves both emergency and preventive maintenance. This thesis analyzes the maintenance records of four supercomputers operational at The National Institute of Computational Science located at Oak Ridge National Laboratory. We propose to use the generalized proportional intensities model (GPIM) to model the maintenance interrupts as it can capture both the reliability parameters and maintenance parameters and allows the inclusion of both emergency and preventive maintenance. …

Identifying Geographical Interdependency In Critical Infrastructure Systems Using Open Source Geospatial Data In Order To Model Restoration Strategies In The Aftermath Of A Large-Scale Disaster, Varun Ramachandran, Tom Shoberg, Suzanna Long, Steven Corns, Hector Carlo

International Journal of Geospatial and Environmental Research

In the wake of a large-scale disaster, strategies for emergency search and rescue, short-term recovery and medium- to long-term restoration are needed. While considerable effort is geared to developing strategies for the former two options, little comprehensive guidance exists on the latter. However, medium- to long-term restoration has a significant effect on local, regional and national economies and is essential to community vitality. In part, the deficit of robust strategies can be linked to the complexity in the data acquisition and limited methodologies to understand the interconnectedness of the relevant systems elements. This research utilizes infrastructure data for Supply Chain …

Towards City-Scale Mobile Crowdsourcing: Task Recommendations Under Trajectory Uncertainties, Chen Cen, Shih-Fen Cheng, Hoong Chuin Lau, Archan Misra

Research Collection School Of Computing and Information Systems

In this work, we investigate the problem of large-scale mobile crowdsourcing, where workers are financially motivated to perform location-based tasks physically. Unlike current industry practice that relies on workers to manually pick tasks to perform, we automatically make task recommendation based on workers’ historical trajectories and desired time budgets. The challenge of predicting workers’ trajectories is that it is faced with uncertainties, as a worker does not take same routes every day. In this work, we depart from deterministic modeling and study the stochastic task recommendation problem where each worker is associated with several predicted routine routes with probabilities. We …

Probabilistic Inference Based Message-Passing For Resource Constrained Dcops, Supriyo Ghosh, Akshat Kumar, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

Distributed constraint optimization (DCOP) is an important framework for coordinated multiagent decision making. We address a practically useful variant of DCOP, called resource-constrained DCOP (RC-DCOP), which takes into account agents’ consumption of shared limited resources. We present a promising new class of algorithm for RC-DCOPs by translating the underlying co- ordination problem to probabilistic inference. Using inference techniques such as expectation- maximization and convex optimization machinery, we develop a novel convergent message-passing algorithm for RC-DCOPs. Experiments on standard benchmarks show that our approach provides better quality than previous best DCOP algorithms and has much lower failure rate. Comparisons against an …

Meta-Raps Hybridization With Machine Learning Algorithms, Fatemah Al-Duoli

Engineering Management & Systems Engineering Theses & Dissertations

This dissertation focuses on advancing the Metaheuristic for Randomized Priority Search algorithm, known as Meta-RaPS, by integrating it with machine learning algorithms. Introducing a new metaheuristic algorithm starts with demonstrating its performance. This is accomplished by using the new algorithm to solve various combinatorial optimization problems in their basic form. The next stage focuses on advancing the new algorithm by strengthening its relatively weaker characteristics. In the third traditional stage, the algorithms are exercised in solving more complex optimization problems. In the case of effective algorithms, the second and third stages can occur in parallel as researchers are eager to …

History-Based Controller Design And Optimization For Partially Observable Mdps, Akshat Kumar, Shlomo Zilberstein

Research Collection School Of Computing and Information Systems

Partially observable MDPs provide an elegant framework forsequential decision making. Finite-state controllers (FSCs) are often used to represent policies for infinite-horizon problems as they offer a compact representation, simple-to-execute plans, and adjustable tradeoff between computational complexityand policy size. We develop novel connections between optimizing FSCs for POMDPs and the dual linear programfor MDPs. Building on that, we present a dual mixed integer linear program (MIP) for optimizing FSCs. To assign well-defined meaning to FSC nodes as well as aid in policy search, we show how to associate history-based features with each FSC node. Using this representation, we address another challenging …

Retail Precinct Management: A Case Of Commercial Decentralization In Singapore, Robert De Souza, Hoong Chuin Lau, Mark Goh, Lindawati, Wee-Siong Ng, Puay-Siew Tan

Research Collection School Of Computing and Information Systems

The synchronized last mile logistics concept seeks to address, through coordinated collaboration, several challenges that hinder reliability, cost efficiency, effective resource planning, scheduling and utilization; and increasingly, sustainability objectives. Subsequently, the meeting of service level and contractual commitments are competitively impacted with any loss of efficiency. These challenges, against a backdrop of Singapore, can essentially be addressed in selected industry sectors through a better understanding of logistics structures; innovative supply chain designs and coordination of services, operations and processes coupled with concerted policies and supply chain strategies.

Development Of A Tridimensional Measuring Application For Ipads, Michael Casebolt, Nicolas Kouatli, Jack Mullen

Computer Science and Software Engineering

In today’s fast-paced distribution centers workers and management alike are constantly searching for the quickest and most efficient way to package items for distribution. Even with the advancement of app-oriented solutions to a variety of problems across many industries there is a distinct unmet need in distribution environments for an application capable of increasing the efficiency and accuracy of packaging items. This senior project focused on the development and testing of an application utilizing the Structure Three Dimensional Sensor and a 4th generation iPad to scan an object or group of objects to be packaged and determine the overall dimensions …

Using The Triple Bottom Line To Select Sustainable Suppliers For A Major Oil And Gas Company, Pandarinath Adarsh Sunkari

Graduate Theses and Dissertations

Companies have primarily been focusing on the financial bottom line i.e., on increasing profits by increasing revenues and reducing costs. With high energy usage and environmental change posing threats to the environment and business operations, companies are now considering sustainability. Since some global suppliers have low cost labor, Social well-being and human development has also emerged as major goals of a company performing global operations. Focusing on these three goals is termed the "Triple Bottom Line" (TBL). We study and explore the TBL benefits that could be realized by an oil and gas company by focusing on sustainable suppliers. A …

Incorporating Environmental And Social Factors Into Decision-Making Of An Oil And Gas Industry To Improve Sustainability, Gaurav Dabhadkar

Graduate Theses and Dissertations

The energy industry (including the oil and gas industry) is facing unparalleled scrutiny and demands from stakeholders including investors, regulators (industry and environmental), communities, and other stakeholders. Sustainable development is one of the major concerns of the oil and gas industry. Companies are seeking to increase sustainability of their operations by considering environmental and Social concerns in addition to economic concerns. Oil and gas companies need to take decisions at different stages of the product life cycle (e.g. planning, design, exploration, production, and clean-up) which have direct or indirect impact on the organization's objectives. Addressing economic, technical, Social, and environmental …

Near-Optimal Decentralized Power Supply Restoration In Smart Grids, Pritee Agrawal, Akshat Kumar, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

Next generation of smart grids face a number of challenges including co-generation from intermittent renewable power sources, a shift away from monolithic control due to increased market deregulation, and robust operation in the face of disasters. Such heterogeneous nature and high operational readiness requirement of smart grids necessitates decentralized control for critical tasks such as power supply restoration (PSR) after line failures. We present a novel multiagent system based approach for PSR using Lagrangian dual decomposition. Our approach works on general graphs, provides provable quality-bounds and requires only local message-passing among different connected sub-regions of a smart grid, enabling decentralized …

Design, Programming, And User-Experience, Kaila G. Manca

Honors Scholar Theses

This thesis is a culmination of my individualized major in Human-Computer Interaction. As such, it showcases my knowledge of design, computer engineering, user-experience research, and puts into practice my background in psychology, com- munications, and neuroscience.

I provided full-service design and development for a web application to be used by the Digital Media and Design Department and their students.This process involved several iterations of user-experience research, testing, concepting, branding and strategy, ideation, and design. It lead to two products.

The first product is full-scale development and optimization of the web appli- cation.The web application adheres to best practices. It was …

Multi-Agent Task Assignment For Mobile Crowdsourcing Under Trajectory Uncertainties, Cen Chen, Shih-Fen Cheng, Hoong Chuin Lau, Archan Misra

Research Collection School Of Computing and Information Systems

In this work, we investigate the problem of mobile crowdsourcing, where workers are financially motivated to perform location-based tasks physically. Unlike current industry practice that relies on workers to manually browse and filter tasks to perform, we intend to automatically make task recommendations based on workers' historical trajectories and desired time budgets. However, predicting workers' trajectories is inevitably faced with uncertainties, as no one will take exactly the same route every day; yet such uncertainties are oftentimes abstracted away in the known literature. In this work, we depart from the deterministic modeling and study the stochastic task recommendation problem where …

Solving Multi-Vehicle Profitable Tour Problem Via Knowledge Adoption In Evolutionary Bi-Level Programming, Stephanus Daniel Handoko, Abhishek Gupta, Chen Kim Heng, Hoong Chuin Lau, Yew Soon Ong, Puay Siew Tan

Research Collection School Of Computing and Information Systems

Profitable tour problem (PTP) belongs to the class of vehicle routing problem (VRP) with profits seeking to maximize the difference between the total collected profit and the total cost incurred. Traditionally, PTP involves single vehicle. In this paper, we consider PTP with multiple vehicles. Unlike the classical VRP that seeks to serve all customers, PTP involves the strategic-level customer selection so as to maximize the total collected profit and the operational-level route optimization to minimize the total cost incurred. Therefore, PTP is essentially the knapsack problem at the strategic level with VRP at the operational level. That means the evolutionary …

Direct: A Scalable Approach For Route Guidance In Selfish Orienteering Problems, Pradeep Varakantham, Hala Mostafa, Na Fu, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

We address the problem of crowd congestion at venues like theme parks, museums and world expos by providing route guidance to multiple selfish users (with budget constraints) moving through the venue simultaneously. To represent these settings, we introduce the Selfish Orienteering Problem (SeOP) that combines two well studied problems from literature, namely Orienteering Problem (OP) and Selfish Routing (SR). OP is a single agent routing problem where the goal is to minimize latency (or maximize reward) in traversing a subset of nodes while respecting budget constraints. SR is a game between selfish agents looking for minimum latency routes from source …