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2020

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Articles 1 - 30 of 112

Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering

A Time Series Sustainability Assessment Of A Partial Energy Portfolio Transition, Jacob Hale, Suzanna Long Dec 2020

A Time Series Sustainability Assessment Of A Partial Energy Portfolio Transition, Jacob Hale, Suzanna Long

Engineering Management and Systems Engineering Faculty Research & Creative Works

Energy portfolios are overwhelmingly dependent on fossil fuel resources that perpetuate the consequences associated with climate change. Therefore, it is imperative to transition to more renewable alternatives to limit further harm to the environment. This study presents a univariate time series prediction model that evaluates sustainability outcomes of partial energy transitions. Future electricity generation at the state-level is predicted using exponential smoothing and autoregressive integrated moving average (ARIMA). The best prediction results are then used as an input for a sustainability assessment of a proposed transition by calculating carbon, water, land, and cost footprints. Missouri, USA was selected as a …

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Solar Photovoltaic Performance Monitoring: A Bibliometric Review, Research Gaps And Opportunities, Javed Sayyad, Paresh Nasikkar Dec 2020

Solar Photovoltaic Performance Monitoring: A Bibliometric Review, Research Gaps And Opportunities, Javed Sayyad, Paresh Nasikkar

Library Philosophy and Practice (e-journal)

Electrical power generation has been revolutionized by growing demand and use of Renewable Energy (RE) sources such as Solar Photovoltaic (SPV) as the main electricity source in modern times. The main objective of this bibliometric analysis is to understand the scope of the literature available for SPV performance characterization. This detailed reviewed was performed on the documents related to SPV research considering all the subject categories from Scopus and Web of Science (WoS) databases. The patterns for the particular set of keywords were broke down with the recuperated outcomes from Scopus database in the language, publication type, year of publication, …

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Comparing Greedy Constructive Heuristic Subtour Elimination Methods For The Traveling Salesman Problem, Petar Jackovich, Bruce A. Cox, Raymond R. Hill Dec 2020

Comparing Greedy Constructive Heuristic Subtour Elimination Methods For The Traveling Salesman Problem, Petar Jackovich, Bruce A. Cox, Raymond R. Hill

Faculty Publications

Purpose — This paper aims to define the class of fragment constructive heuristics used to compute feasible solutions for the traveling salesman problem (TSP) into edge-greedy and vertex-greedy subclasses. As these subclasses of heuristics can create subtours, two known methodologies for subtour elimination on symmetric instances are reviewed and are expanded to cover asymmetric problem instances. This paper introduces a third novel subtour elimination methodology, the greedy tracker (GT), and compares it to both known methodologies. Design/methodology/approach — Computational results for all three subtour elimination methodologies are generated across 17 symmetric instances ranging in size from 29 vertices to 5,934 …

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Scenario Analysis Of Downtown One-Way Street Conversions In Lincoln, Nebraska: A Case Study For Downtown Livability And Pedestrian Safety, Terrence Lage Dec 2020

Scenario Analysis Of Downtown One-Way Street Conversions In Lincoln, Nebraska: A Case Study For Downtown Livability And Pedestrian Safety, Terrence Lage

Community and Regional Planning Program: Theses and Student Projects

An era of downtown street design benefiting the automobile has become over designed for the movement of volumes of traffic in many North American cities. Since the 1950s, the primary focus of planners and traffic engineers has been to address the growing problem of traffic congestion caused by the suburban traveler coming into and out of downtown. The solution was retrofitting the original two-way street grid into a network of wide and straight multi-lane one-way corridors. This design successfully moved volumes of traffic through downtown streets but induced behavior to favor the automobile instead of design that favors active mobility …

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Optimal Collaborative Path Planning For Unmanned Surface Vehicles Carried By A Parent Boat Along A Planned Route, Ari Carisza Graha Prasetia, I-Lin Wang, Aldy Gunawan Dec 2020

Optimal Collaborative Path Planning For Unmanned Surface Vehicles Carried By A Parent Boat Along A Planned Route, Ari Carisza Graha Prasetia, I-Lin Wang, Aldy Gunawan

Research Collection School Of Computing and Information Systems

In this paper, an effective mechanism using a fleet of unmanned surface vehicles (USVs) carried by a parent boat (PB) is proposed to complete search or scientific tasks over multiple target water areas within a shorter time . Specifically, multiple USVs can be launched from the PB to conduct such operations simultaneously, and each USV can return to the PB for battery recharging or swapping and data collection in order to continue missions in a more extended range. The PB itself follows a planned route with a flexible schedule taking into consideration locational constraints or collision avoidance in a real-world …

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Improvement Of Light Intensity And Efficiency Of N-Zno/Nio/P-Gan Heterojunction-Based White Light Emitting Diodes Using Micro-/Nanolens Array, Apurba Adhikary, Md Shamim Ahsan, Md Mahbub Hossain, Md Bipul Hossain, S. H. Shah Newaz, Farid Ahmed, Ik-Bu Sohn Nov 2020

Improvement Of Light Intensity And Efficiency Of N-Zno/Nio/P-Gan Heterojunction-Based White Light Emitting Diodes Using Micro-/Nanolens Array, Apurba Adhikary, Md Shamim Ahsan, Md Mahbub Hossain, Md Bipul Hossain, S. H. Shah Newaz, Farid Ahmed, Ik-Bu Sohn

Manufacturing & Industrial Engineering Faculty Publications and Presentations

Our study proposes a technique to enhance light extraction efficiency of light emitting diodes (LEDs) by incorporating various micro-/nanolens arrays (MNLAs) on the substrate layer, which in turn increases the external quantum efficiency (EQE) of the LEDs. To simulate the LEDs, we utilized the finite difference time domain method. To achieve a white LED, we inserted a thin layer of NiO at the interface between the n-type ZnO and the p-type GaN. The basic n-ZnO/NiO/p-GaN heterojunction-based LED exhibited an EQE of 10.99% where the effective refractive index of the LED structure was 1.48. The EQE was further increased by engraving …

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Demystifying Artificial Intelligence Based Digital Twins In Manufacturing- A Bibliometric Analysis Of Trends And Techniques, Satish Kumar, Shruti Patil, Arunkumar Bongale, Ketan Kotecha, Anup Kumar M. Bongale, Pooja Kamat Nov 2020

Demystifying Artificial Intelligence Based Digital Twins In Manufacturing- A Bibliometric Analysis Of Trends And Techniques, Satish Kumar, Shruti Patil, Arunkumar Bongale, Ketan Kotecha, Anup Kumar M. Bongale, Pooja Kamat

Library Philosophy and Practice (e-journal)

Nowadays, data is considered as a new life force for operations of physical systems in various domains such as manufacturing, healthcare, transportations, etc. However, the hugely generated data, which mirrors the working essence of the product life cycle, is still underutilised. Digital Twin (DT), a collective representation of active and passive captured data, is a virtual counterpart of the physical resources that could help prevent effective preventive maintenance in any applied domain. Currently, lots of research is going on about the applicability of digital twin in smart IOT based manufacturing industry 4.0 environment. Still, it lacks a formal study, which …

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Grow Local Manufacturing Along Us/Mexico Border Region For An Integrated Supply Chain In The Post Covid-19 Era, Jianzhi Li Nov 2020

Grow Local Manufacturing Along Us/Mexico Border Region For An Integrated Supply Chain In The Post Covid-19 Era, Jianzhi Li

Manufacturing & Industrial Engineering Faculty Publications and Presentations

The current coronavirus disease pandemic, plus the strong movement of manufacturing reshoring, provide a unique opportunity for many US regions to grow local manufacturers. This technical note attempts to review the current situation and trend in US manufacturing. We then discuss challenges and necessary steps, such as asset mapping, required to grow local suppliers. Suggestions are then made to support growing local suppliers along the US/Mexico border region.

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Sports Analytics: Putting The Fun Back Into Analytics, Walt Degrange Nov 2020

Sports Analytics: Putting The Fun Back Into Analytics, Walt Degrange

Operations Management Presentations

With the recent success of sports teams heavily using analytics (Dodgers, Patriots, Capitals, Warriors, Leicester City F.C.), does this mean that analytics has gained a foothold in the sports world? I use a k-means clustering model to determine if performance since 2015 in the four major US sports can support this question. And is there a career path that a high school student can use to become a sports analytics professional? This presentation attempts to answer that question by exploring all the areas of the application of analytics in sports. The final point the brief makes is that by using …

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Civilian Pepper Spray For Self Defense: Understanding User Perception And Impact Of Design On User Performance, David Strybel, Anil R. Kumar Nov 2020

Civilian Pepper Spray For Self Defense: Understanding User Perception And Impact Of Design On User Performance, David Strybel, Anil R. Kumar

Faculty Publications

Pepper spray is widely used in the US, and is marketed as an effective self-defense device. While pepper spray can be useful in deterring an attacker, many pepper spray owners do not have any experience using it. There is a dearth of published studies that focus on civilian pepper-spray use, not to mention first time pepper-spray users. A study to analyze pepper-spray designs with first-time users, to see how the design, specifically the safety mechanism, affects response time and overall performance would be helpful. The study was conducted in 2 parts – a survey to understand user perception, and a …

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Rural Access To Industry 4.0: Barriers From The Infrastructure Planning Front Lines, Javier Valentin-Sivico, Casey I. Canfield, Ona Egbue Nov 2020

Rural Access To Industry 4.0: Barriers From The Infrastructure Planning Front Lines, Javier Valentin-Sivico, Casey I. Canfield, Ona Egbue

Engineering Management and Systems Engineering Faculty Research & Creative Works

Many rural communities lack adequate broadband infrastructure, which limits the economic development potential in these regions. They are not able to attract new businesses, and established businesses are unable to use tools and services that require high-speed internet. Broadband access is a requirement for the Internet of Things, robotics, and big data, which are part of Industry 4.0 and the future economy. Such technological advances are not only transforming the manufacturing environments and the service industry, but also finding applications in the food supply chain, such as precision agriculture. In this study, we conducted 17 semi-structured interviews (11 reported here) …

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A Markov Chain Approach For Forecasting Progression Of Opioid Addiction, Abhijit Gosavi, Susan L. Murray, N. Karagiannis Nov 2020

A Markov Chain Approach For Forecasting Progression Of Opioid Addiction, Abhijit Gosavi, Susan L. Murray, N. Karagiannis

Engineering Management and Systems Engineering Faculty Research & Creative Works

The U.S. is currently facing an opioid crisis. Naltrexone is a common treatment for drug addiction; it reduces the desire to take opiates. However, addicts often stop treatment or continue to use opioids while in treatment. This results in increased fatalities and associated costs. A Markov-chain model is presented to analyze the progression of opioid addiction to assist the medical community in developing appropriate treatments. The model includes patients who continue opiate use while on naltrexone (blocked patients) and those who use opiates after missing naltrexone doses (unblocked patients). The other types of patients are abstinent (the best-case scenario) and …

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Macroeconomic Aspects Of Maintenance Optimization Of Critical Infrastructures, S. A. Timashev, A. V. Bushinskaya Nov 2020

Macroeconomic Aspects Of Maintenance Optimization Of Critical Infrastructures, S. A. Timashev, A. V. Bushinskaya

Engineering Management & Systems Engineering Faculty Publications

The main goal of maintenance is prevention, timely detection and elimination of failures and damage. From the point of view of critical infrastructures (CIs), the main purpose of their maintenance is to increase the safety of CIs and / or to ensure life safety. CIs should be optimal in terms of their purpose, cost, as a source of income and profit at all stages of their life cycle, and also acceptable in terms of possible loss of human lives or injuries. The paper considers the assessment of necessary optimal investments in the maintenance (time interval between subsequent maintenance), to increase …

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Black-Swan Type Catastrophes And Antifragility/Supra-Resilience Of Urban Socio-Technical Infrastructures, S. A, Timashev Nov 2020

Black-Swan Type Catastrophes And Antifragility/Supra-Resilience Of Urban Socio-Technical Infrastructures, S. A, Timashev

Engineering Management & Systems Engineering Faculty Publications

This paper may be one of the first attempts dealing with the problem of creating, providing and maintaining antifragility of systems of interdependent urban critical infrastructures (CI) in the wake of black-swan type technological, ecological, economic or social catastrophes occurring in a municipality. A synonym is offered to describe antifragility from a positive psychology perspective, formulating the problem as the supraresilience problem. A brief description is given of the developed innovative approach for creating a supraresilient city/region using black-swan catastrophe and the antifragility concepts. Resilience metrics are formulated as well as methods of assessing damage, interdependence of infrastructures and convergent …

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Communicating Uncertain Information From Deep Learning Models In Human Machine Teams, Harishankar V. Subramanian, Casey I. Canfield, Daniel Burton Shank, Luke Andrews, Cihan H. Dagli Oct 2020

Communicating Uncertain Information From Deep Learning Models In Human Machine Teams, Harishankar V. Subramanian, Casey I. Canfield, Daniel Burton Shank, Luke Andrews, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

The role of human-machine teams in society is increasing, as big data and computing power explode. One popular approach to AI is deep learning, which is useful for classification, feature identification, and predictive modeling. However, deep learning models often suffer from inadequate transparency and poor explainability. One aspect of human systems integration is the design of interfaces that support human decision-making. AI models have multiple types of uncertainty embedded, which may be difficult for users to understand. Humans that use these tools need to understand how much they should trust the AI. This study evaluates one simple approach for communicating …

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Characterization And Performance Of Minimum Quantity Lubricants In Through-Tool Drilling, Amla Patil, Jay Raval, Tim Bangma, Immanuel Edinbarough, Bruce Tai, David Stephenson, Suleiman Obeidat, Wayne Nguyen Hung Oct 2020

Characterization And Performance Of Minimum Quantity Lubricants In Through-Tool Drilling, Amla Patil, Jay Raval, Tim Bangma, Immanuel Edinbarough, Bruce Tai, David Stephenson, Suleiman Obeidat, Wayne Nguyen Hung

Manufacturing & Industrial Engineering Faculty Publications and Presentations

This study characterized airborne microdroplet diameters and size distribution from two commercially available lubricants A and B for internal minimum quantity lubrication (MQL). The effects of air pressure, oil channel size, physical properties of lubricants on the resultant microdroplets and through-tool MQL drilling performance were studied. Airborne microdroplet diameters were highly sensitive to the coolant channel sizes and air pressure. Cluster method was used to divide microdroplets into smaller clusters for comparison. Experimental data show that the average airborne microdroplet of lubricant B was larger than that of lubricant A at different air pressures and channel sizes. The contact angle …

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Cost Estimating Using A New Learning Curve Theory For Non-Constant Production Rates, Dakotah Hogan, John J. Elshaw, Clay M. Koschnick, Jonathan D. Ritschel, Adedeji B. Badiru, Shawn M. Valentine Oct 2020

Cost Estimating Using A New Learning Curve Theory For Non-Constant Production Rates, Dakotah Hogan, John J. Elshaw, Clay M. Koschnick, Jonathan D. Ritschel, Adedeji B. Badiru, Shawn M. Valentine

Faculty Publications

Traditional learning curve theory assumes a constant learning rate regardless of the number of units produced. However, a collection of theoretical and empirical evidence indicates that learning rates decrease as more units are produced in some cases. These diminishing learning rates cause traditional learning curves to underestimate required resources, potentially resulting in cost overruns. A diminishing learning rate model, namely Boone’s learning curve, was recently developed to model this phenomenon. This research confirms that Boone’s learning curve systematically reduced error in modeling observed learning curves using production data from 169 Department of Defense end-items. However, high amounts of variability in …

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The Application Of Fuzzy Analytic Hierarchy Process In Sustainable Project Selection, Rakan Alyamani, Suzanna Long Oct 2020

The Application Of Fuzzy Analytic Hierarchy Process In Sustainable Project Selection, Rakan Alyamani, Suzanna Long

Engineering Management and Systems Engineering Faculty Research & Creative Works

The project selection process is a crucial step in sustainable development. Effective sustainable development depends on the ability to select the appropriate sustainable project to implement to ensure that the desired goals are met. Some of the most common characteristics or criteria used in evaluating sustainable projects include novelty, uncertainty, skill and experience, technology information transfer, and project cost. Prioritizing these criteria based on relative importance helps project managers and decision makers identify elements that require additional attention, better allocate resources, as well as improve the selection process when evaluating different sustainable project alternatives. The aim of this research is …

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Change Management: Increasing The Odds Of Adoption, Travis Mcneal Oct 2020

Change Management: Increasing The Odds Of Adoption, Travis Mcneal

Operations Management Presentations

With rapid changes happening all around, organizations are finding themselves in positions where they need their workforce to adapt to new ways of working (technology, structural, process). Organizations develop strategies, programs and projects intended to address these changes. Unfortunately, history is littered with strategies and programs that fail to live deliver on expected results. This has led to the recent rise and proliferation of Change Management as a practice and skill set. Often times, however, Change Management theory is given preeminence over practicality. This webinar will explore practical and actionable ways you can take to immediately increase the odds …

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United States Department Of Defense (Dod) Real Property Repair, Alterations, Maintenance, And Construction Project Contract Data: 2009–2020, Tyler Stout, Adam Teston, Brent T. Langhals, Justin D. Delorit, Carlton Hendrix, Steven J. Schuldt Oct 2020

United States Department Of Defense (Dod) Real Property Repair, Alterations, Maintenance, And Construction Project Contract Data: 2009–2020, Tyler Stout, Adam Teston, Brent T. Langhals, Justin D. Delorit, Carlton Hendrix, Steven J. Schuldt

Faculty Publications

Nearly one-half of all construction projects exceed planned costs and schedule, globally [1]. Owners and construction managers can analyze historical project performance data to inform cost and schedule overrun risk-reduction strategies. Though, the majority of open-source project datasets are limited by the number of projects, data dimensionality, and location. A significant global customer of the construction industry, the Department of Defense (DoD) maintains a vast database of historical project data that can be used to determine the sources and magnitude of construction schedule and cost overruns for many continental and international locations. The selection of data provided by the authors …

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Deep Reinforcement Learning Approach To Solve Dynamic Vehicle Routing Problem With Stochastic Customers, Waldy Joe, Hoong Chuin Lau Oct 2020

Deep Reinforcement Learning Approach To Solve Dynamic Vehicle Routing Problem With Stochastic Customers, Waldy Joe, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

In real-world urban logistics operations, changes to the routes and tasks occur in response to dynamic events. To ensure customers’ demands are met, planners need to make these changes quickly (sometimes instantaneously). This paper proposes the formulation of a dynamic vehicle routing problem with time windows and both known and stochastic customers as a route-based Markov Decision Process. We propose a solution approach that combines Deep Reinforcement Learning (specifically neural networks-based TemporalDifference learning with experience replay) to approximate the value function and a routing heuristic based on Simulated Annealing, called DRLSA. Our approach enables optimized re-routing decision to be generated …

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Online Traffic Signal Control Through Sample-Based Constrained Optimization, Srishti Dhamija, Alolika Gon, Pradeep Varakantham, William Yeoh Oct 2020

Online Traffic Signal Control Through Sample-Based Constrained Optimization, Srishti Dhamija, Alolika Gon, Pradeep Varakantham, William Yeoh

Research Collection School Of Computing and Information Systems

Traffic congestion reduces productivity of individuals by increasing time spent in traffic and also increases pollution. To reduce traffic congestion by better handling dynamic traffic patterns, recent work has focused on online traffic signal control. Typically, the objective in traffic signal control is to minimize expected delay over all vehicles given the uncertainty associated with the vehicle turn movements at intersections. In order to ensure responsiveness in decision making, a typical approach is to compute a schedule that minimizes the delay for the expected scenario of vehicle movements instead of minimizing expected delay over the feasible vehicle movement scenarios. Such …

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Resilient Design And Crisis Management, Rich Ham Sep 2020

Resilient Design And Crisis Management, Rich Ham

Operations Management Presentations

Explores the techniques to design resilience into systems, business functions, compliance, quality assurance and response to uncertainty. Includes an overview of Federal Emergency Management Agency principles in resilient design and crisis management, including implementation of National Incident Management System processes and industry standards to frame resilient design, procedures and planning documents. Learn to focus on the use of testing, exercises, and implementation of Plan, Do, Check, Act model to continually improve government, business and personal continuity through periods of cascading uncertainty.

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Knowledge Based View Of University Tech Transfer—A Systematic Literature Review And Meta-Analysis, Clovia Hamilton, Philbin P. Simon Sep 2020

Knowledge Based View Of University Tech Transfer—A Systematic Literature Review And Meta-Analysis, Clovia Hamilton, Philbin P. Simon

Technology & Society Faculty Publications

Research and technology commercialization at research-intensive universities has helped to develop provincial economies resulting in university startups, the growth of other new companies and associated employment. University technology transfer offices (TTOs) oversee the process of technology transfer into the commercial marketplace and these organizational units can be considered in the context of enabling effective knowledge management. However, what enables productive TTO performance has not been comprehensively researched. Therefore, this research study adopted the knowledge-based view as the theoretical construct to support a comprehensive investigation into this area. This was achieved through employing a systematic literature review (SLR) combined with a …

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Cost Analysis Of Optimized Islanded Energy Systems In A Dispersed Air Base Conflict, Jay F. Pearson, Torrey J. Wagner, Justin D. Delorit Sep 2020

Cost Analysis Of Optimized Islanded Energy Systems In A Dispersed Air Base Conflict, Jay F. Pearson, Torrey J. Wagner, Justin D. Delorit

Faculty Publications

The United States Air Force has implemented a dispersed air base strategy to enhance mission effectiveness for near-peer conflicts. Asset dispersal places many smaller bases across a wide geographic area, which increases resupply requirements and logistical complexity. Hybrid energy systems reduce resupply requirements through sustainable, off-grid energy production. This paper presents a novel hybrid energy renewable delivery system (HERDS) model capable of (1) selecting the optimal hybrid energy system design that meets demand at the lowest net present cost and (2) optimizing the delivery of the selected system using existing Air Force cargo aircraft. The novelty of the model’s capabilities …

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Strategic Decision Facilitation: Supporting Critical Assumptions Of The Human In Empirical Modeling Of Pairwise Value Comparisons, Joseph P. Kristbaum, Frank W. Ciarallo Sep 2020

Strategic Decision Facilitation: Supporting Critical Assumptions Of The Human In Empirical Modeling Of Pairwise Value Comparisons, Joseph P. Kristbaum, Frank W. Ciarallo

Faculty Publications

Modeling human decision-making is difficult. Decision-makers are typically primed with unique biases that widen the confidence interval of judgment. Therefore, it is important that the human process in the system being modeled is designed to alleviate damaging biases and assumptions in an effort to increase process consistency between decision-makers. In this experiment, it is hypothesized that coupling specific decision-facilitation methods with a specific scale range will affect the consistency between decision-makers. This article presents a multiphase experiment that examines a varying presentation mode as well as scale range to determine how value is determined in subsequent pairwise comparisons of alternatives …

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Bus Frequency Optimization: When Waiting Time Matters In User Satisfaction, Songsong Mo, Zhifeng Bao, Baihua Zheng, Zhiyong Peng Sep 2020

Bus Frequency Optimization: When Waiting Time Matters In User Satisfaction, Songsong Mo, Zhifeng Bao, Baihua Zheng, Zhiyong Peng

Research Collection School Of Computing and Information Systems

Reorganizing bus frequency to cater for the actual travel demand can save the cost of the public transport system significantly. Many, if not all, existing studies formulate this as a bus frequency optimization problem which tries to minimize passengers’ average waiting time. However, many investigations have confirmed that the user satisfaction drops faster as the waiting time increases. Consequently, this paper studies the bus frequency optimization problem considering the user satisfaction. Specifically, for the first time to our best knowledge, we study how to schedule the buses such that the total number of passengers who could receive their bus services …

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Zone Path Construction (Zac) Based Approaches For Effective Real-Time Ridesharing, Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet Sep 2020

Zone Path Construction (Zac) Based Approaches For Effective Real-Time Ridesharing, Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet

Research Collection School Of Computing and Information Systems

Real-time ridesharing systems such as UberPool, Lyft Line, GrabShare have become hugely popular as they reduce the costs for customers, improve per trip revenue for drivers and reduce traffic on the roads by grouping customers with similar itineraries. The key challenge in these systems is to group the "right" requests to travel together in the "right" available vehicles in real-time, so that the objective (e.g., requests served, revenue or delay) is optimized. This challenge has been addressed in existing work by: (i) generating as many relevant feasible (with respect to the available delay for customers) combinations of requests as possible …

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A Genetic Algorithm To Minimise Number Of Vehicles In An Electric Vehicle Routing Problem, Kiian Leong Bertran Queck, Hoong Chuin Lau Sep 2020

A Genetic Algorithm To Minimise Number Of Vehicles In An Electric Vehicle Routing Problem, Kiian Leong Bertran Queck, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Electric Vehicles (EVs) and charging infrastructure are starting to become commonplace in major cities around the world. For logistics providers to adopt an EV fleet, there are many factors up for consideration, such as route planning for EVs with limited travel range as well as long-term planning of fleet size. In this paper, we present a genetic algorithm to perform route planning that minimises the number of vehicles required. Specifically, we discuss the challenges on the violations of constraints in the EV routing problem (EVRP) arising from applying genetic algorithm operators. To overcome the challenges, techniques specific to addressing the …

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A Hybrid Framework Using A Qubo Solver For Permutation-Based Combinatorial Optimization, Siong Thye Goh, Sabrish Gopalakrishnan, Jianyuan Bo, Hoong Chuin Lau Sep 2020

A Hybrid Framework Using A Qubo Solver For Permutation-Based Combinatorial Optimization, Siong Thye Goh, Sabrish Gopalakrishnan, Jianyuan Bo, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

In this paper, we propose a hybrid framework to solve large-scale permutation-based combinatorial problems effectively using a high-performance quadratic unconstrained binary optimization (QUBO) solver. To do so, transformations are required to change a constrained optimization model to an unconstrained model that involves parameter tuning. We propose techniques to overcome the challenges in using a QUBO solver that typically comes with limited numbers of bits. First, to smooth the energy landscape, we reduce the magnitudes of the input without compromising optimality. We propose a machine learning approach to tune the parameters for good performance effectively. To handle possible infeasibility, we introduce …

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