Matching Items (51)
Description
This thesis was conducted to study and analyze the fund allocation process adopted by different states in the United States to reduce the impact of the Covid-19 virus. Seven different states and their funding methodologies were compared against the case count within the state. The study also focused on development of a physical distancing index based on three significant attributes. This index was then compared to the expenditure and case counts to support decision making.
A regression model was developed to analyze and compare how different states case counts played out against the regression model and the risk index.
ContributorsJaisinghani, Shaurya (Author) / Mirchandani, Pitu (Thesis director) / Clough, Michael (Committee member) / McCarville, Daniel R. (Committee member) / Industrial, Systems & Operations Engineering Prgm (Contributor) / Department of Information Systems (Contributor) / Industrial, Systems & Operations Engineering Prgm (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
In this dissertation, an innovative framework for designing a multi-product integrated supply chain network is proposed. Multiple products are shipped from production facilities to retailers through a network of Distribution Centers (DCs). Each retailer has an independent, random demand for multiple products. The particular problem considered in this study also involves mixed-product transshipments between DCs with multiple truck size selection and routing delivery to retailers. Optimally solving such an integrated problem is in general not easy due to its combinatorial nature, especially when transshipments and routing are involved. In order to find out a good solution effectively, a two-phase solution methodology is derived: Phase I solves an integer programming model which includes all the constraints in the original model except that the routings are simplified to direct shipments by using estimated routing cost parameters. Then Phase II model solves the lower level inventory routing problem for each opened DC and its assigned retailers. The accuracy of the estimated routing cost and the effectiveness of the two-phase solution methodology are evaluated, the computational performance is found to be promising. The problem is able to be heuristically solved within a reasonable time frame for a broad range of problem sizes (one hour for the instance of 200 retailers). In addition, a model is generated for a similar network design problem considering direct shipment and consolidation within the same product set opportunities. A genetic algorithm and a specific problem heuristic are designed, tested and compared on several realistic scenarios.
ContributorsXia, Mingjun (Author) / Askin, Ronald (Thesis advisor) / Mirchandani, Pitu (Committee member) / Zhang, Muhong (Committee member) / Kierstead, Henry (Committee member) / Arizona State University (Publisher)
Created2013
Description
With the rapid development of mobile sensing technologies like GPS, RFID, sensors in smartphones, etc., capturing position data in the form of trajectories has become easy. Moving object trajectory analysis is a growing area of interest these days owing to its applications in various domains such as marketing, security, traffic monitoring and management, etc. To better understand movement behaviors from the raw mobility data, this doctoral work provides analytic models for analyzing trajectory data. As a first contribution, a model is developed to detect changes in trajectories with time. If the taxis moving in a city are viewed as sensors that provide real time information of the traffic in the city, a change in these trajectories with time can reveal that the road network has changed. To detect changes, trajectories are modeled with a Hidden Markov Model (HMM). A modified training algorithm, for parameter estimation in HMM, called m-BaumWelch, is used to develop likelihood estimates under assumed changes and used to detect changes in trajectory data with time. Data from vehicles are used to test the method for change detection. Secondly, sequential pattern mining is used to develop a model to detect changes in frequent patterns occurring in trajectory data. The aim is to answer two questions: Are the frequent patterns still frequent in the new data? If they are frequent, has the time interval distribution in the pattern changed? Two different approaches are considered for change detection, frequency-based approach and distribution-based approach. The methods are illustrated with vehicle trajectory data. Finally, a model is developed for clustering and outlier detection in semantic trajectories. A challenge with clustering semantic trajectories is that both numeric and categorical attributes are present. Another problem to be addressed while clustering is that trajectories can be of different lengths and also have missing values. A tree-based ensemble is used to address these problems. The approach is extended to outlier detection in semantic trajectories.
ContributorsKondaveeti, Anirudh (Author) / Runger, George C. (Thesis advisor) / Mirchandani, Pitu (Committee member) / Pan, Rong (Committee member) / Maciejewski, Ross (Committee member) / Arizona State University (Publisher)
Created2012
Description
Public Private Partnerships (PPP) have been in use for years in the United Kingdom, Europe, Australia and for a shorter time here in the United States. Typical PPP infrastructure projects include a multi-year term of operation in addition to constructing the structural features to be used. Early studies are proving PPP delivery methods to be effective at construction cost containment. An examination of the key elements that constitute the early stage negotiation reveal that there is room for negotiation created by the governing documentation while maintaining a competitive environment that brings the best value available to the Public entity. This paper will examine why PPP's are effective during this critical construction period of the facilities life cycle. It is the intent of this study to examine why the features and outcomes of more or less negotiation and the degree of rigor associated with it.
ContributorsMaddex, William E (Author) / Chasey, Allan (Thesis advisor) / El Asmar, Mounir (Committee member) / Pendyala, Ram (Committee member) / Arizona State University (Publisher)
Created2012
Description
The main objective of this research is to develop an integrated method to study emergent behavior and consequences of evolution and adaptation in engineered complex adaptive systems (ECASs). A multi-layer conceptual framework and modeling approach including behavioral and structural aspects is provided to describe the structure of a class of engineered complex systems and predict their future adaptive patterns. The approach allows the examination of complexity in the structure and the behavior of components as a result of their connections and in relation to their environment. This research describes and uses the major differences of natural complex adaptive systems (CASs) with artificial/engineered CASs to build a framework and platform for ECAS. While this framework focuses on the critical factors of an engineered system, it also enables one to synthetically employ engineering and mathematical models to analyze and measure complexity in such systems. In this way concepts of complex systems science are adapted to management science and system of systems engineering. In particular an integrated consumer-based optimization and agent-based modeling (ABM) platform is presented that enables managers to predict and partially control patterns of behaviors in ECASs. Demonstrated on the U.S. electricity markets, ABM is integrated with normative and subjective decision behavior recommended by the U.S. Department of Energy (DOE) and Federal Energy Regulatory Commission (FERC). The approach integrates social networks, social science, complexity theory, and diffusion theory. Furthermore, it has unique and significant contribution in exploring and representing concrete managerial insights for ECASs and offering new optimized actions and modeling paradigms in agent-based simulation.
ContributorsHaghnevis, Moeed (Author) / Askin, Ronald G. (Thesis advisor) / Armbruster, Dieter (Thesis advisor) / Mirchandani, Pitu (Committee member) / Wu, Tong (Committee member) / Hedman, Kory (Committee member) / Arizona State University (Publisher)
Created2013
Description
Public-Private Partnerships (P3) in North America have become a trend in the past two decades and are gaining attention in the transportation industry with some large scale projects being delivered by this approach. This is due to the need for alternative funding sources for public projects and for improved efficiency of these projects in order to save time and money. Several research studies have been done, including mature markets in Europe and Australia, on the cost and schedule performance of transportation projects but no similar study has been conducted in North America. This study focuses on cost and schedule performance of twelve P3 transportation projects during their construction phase, costing over $100 million each, consisting of roads and bridges only with no signature tunnels. The P3 approach applied in this study is the Design-Build-Finance-Operate-Maintain (DBFOM) model and the results obtained are compared with similar research studies on North American Design-Build (DB) and Design-Bid-Build (DBB) projects. The schedule performance for P3 projects in this study was found to be -0.23 percent versus estimated as compared to the 4.34 percent for the DBB projects and 11.04 percent for the DB projects in the Shrestha study, indicating P3 projects are completed in less time than other methods. The cost performance in this study was 0.81 percent for the P3 projects while in the Shrestha study the average cost increase for the four DB projects was found to be 1.49 percent while for the DBB projects it was 12.71 percent, again indicating P3 projects reduce cost compared to other delivery approaches. The limited number of projects available for this study does not allow us to draw an explicit conclusion on the performance of P3s in North America but paves the way for future studies to explore more data as it becomes available. However, the results in this study show that P3 projects have good cost and schedule adherence to the contract requirements. This study gives us an initial comparison of P3 performance with the more traditional approach and shows us the empirical benefits and limitations of the P3 approach in the highway construction industry.
ContributorsBansal, Ankita (Author) / Chasey, Allan (Thesis advisor) / Gibson, Edd (Committee member) / Pendyala, Ram (Committee member) / Arizona State University (Publisher)
Created2012
Description
Today's competitive markets force companies to constantly engage in the complex task of managing their demand. In make-to-order manufacturing or service systems, the demand of a product is shaped by price and lead times, where high price and lead time quotes ensure profitability for supplier, but discourage the customers from placing orders. Low price and lead times, on the other hand, generally result in high demand, but do not necessarily ensure profitability. The price and lead time quotation problem considers the trade-off between offering high and low prices and lead times. The recent practices in make-to- order manufacturing companies reveal the importance of dynamic quotation strategies, under which the prices and lead time quotes flexibly change depending on the status of the system. In this dissertation, the objective is to model a make-to-order manufacturing system and explore various aspects of dynamic quotation strategies such as the behavior of optimal price and lead time decisions, the impact of customer preferences on optimal decisions, the benefits of employing dynamic quotation in comparison to simpler quotation strategies, and the benefits of coordinating price and lead time decisions. I first consider a manufacturer that receives demand from spot purchasers (who are quoted dynamic price and lead times), as well as from contract customers who have agree- ments with the manufacturer with fixed price and lead time terms. I analyze how customer preferences affect the optimal price and lead time decisions, the benefits of dynamic quo- tation, and the optimal mix of spot purchaser and contract customers. These analyses necessitate the computation of expected tardiness of customer orders at the moment cus- tomer enters the system. Hence, in the second part of the dissertation, I develop method- ologies to compute the expected tardiness in multi-class priority queues. For the trivial single class case, a closed formulation is obtained. For the more complex multi-class case, numerical inverse Laplace transformation algorithms are developed. In the last part of the dissertation, I model a decentralized system with two components. Marketing department determines the price quotes with the objective of maximizing revenues, and manufacturing department determines the lead time quotes to minimize lateness costs. I discuss the ben- efits of coordinating price and lead time decisions, and develop an incentivization scheme to reduce the negative impacts of lack of coordination.
ContributorsHafizoglu, Ahmet Baykal (Author) / Gel, Esma S (Thesis advisor) / Villalobos, Jesus R (Committee member) / Mirchandani, Pitu (Committee member) / Keskinocak, Pinar (Committee member) / Runger, George C. (Committee member) / Arizona State University (Publisher)
Created2012
Description
The Phoenix-Metro area currently has problems with its transportation systems. Over-crowded and congested freeways have slowed travel times within the area. Express bus transportation and the existence of "High Occupancy" lanes have failed to solve the congestion problem. The light rail system is limited to those within a certain distance from the line, and even the light rail is either too slow or too infrequent for a commuter to utilize it effectively. To add to the issue, Phoenix is continuing to expand outward instead of increasing population density within the city, therefore increasing the time it takes to travel to downtown Phoenix, which is the center of economic activity. The people of Phoenix and its surrounding areas are finding that driving themselves to work is just as cost-effective and less time consuming than taking public transportation. Phoenix needs a cost-effective solution to work in co- existence with improvements in local public transportation that will allow citizens to travel to their destination in just as much time, or less time, than travelling by personal vehicle.
ContributorsSerfilippi, Jon (Author) / Ariaratnam, Samuel (Thesis director) / Pendyala, Ram (Committee member) / Pembroke, Jim (Committee member) / Barrett, The Honors College (Contributor) / Ira A. Fulton School of Engineering (Contributor)
Created2012-12
Description
Transit-oriented developments (TODs) are a promising strategy to increase public transit use and, as a result, reduce personal car travel. By using TOD infill to increase urban population density and encourage transportation mode-shifting, the potential exists to reduce life-cycle per capita energy use and environmental impacts of the interdependent infrastructure systems. This project specifically examined the Gold Line of light rail and Orange Line of bus rapid transit in Los Angeles, CA.
ContributorsNahlik, Matthew John (Author) / Chester, Mikhail (Thesis director) / Pendyala, Ram (Committee member) / Pincetl, Stephanie (Committee member) / Civil, Environmental and Sustainable Engineering Programs (Contributor) / Barrett, The Honors College (Contributor) / School of Sustainability (Contributor)
Created2013-05
Description
Approximately 1% of the total working population within the United States bikes as their primary mode of commute. Due to recent increased in bicycle facilities as well as a focus on alternative modes of transport, understanding the motivations and type of people who bike to work is important in order to encourage new users.
In this project, a literature review was completed as well as data analysis of the National Household Travel Survey (NHTS) in order to find specific populations to target. Using these target populations, it is suggested that advertising and workplace encouragement occur to persuade more people to bike to work. Through data analysis it was found that the most impactful variables were the region of the country, gender, population density, and commute distance. Bicycle commuters statistically had fewer vehicles in their households and drove less miles annually.
There were five main target groups found through this analysis; people who bike for other reasons besides work and live in a city with more than 4,000 people per square mile, young professionals between 19-39, women in regions with separated bicycle facilities, those with low vehicle availability, and environmentally conscious individuals. Working to target these groups through advertising campaigns to encourage new users, as well as increasing and improving bicycle facilities, will help create more new bicyclists.
In this project, a literature review was completed as well as data analysis of the National Household Travel Survey (NHTS) in order to find specific populations to target. Using these target populations, it is suggested that advertising and workplace encouragement occur to persuade more people to bike to work. Through data analysis it was found that the most impactful variables were the region of the country, gender, population density, and commute distance. Bicycle commuters statistically had fewer vehicles in their households and drove less miles annually.
There were five main target groups found through this analysis; people who bike for other reasons besides work and live in a city with more than 4,000 people per square mile, young professionals between 19-39, women in regions with separated bicycle facilities, those with low vehicle availability, and environmentally conscious individuals. Working to target these groups through advertising campaigns to encourage new users, as well as increasing and improving bicycle facilities, will help create more new bicyclists.
ContributorsImbus, Eileen Elizabeth (Author) / Khoeini, Sara (Thesis director) / Pendyala, Ram (Committee member) / Civil, Environmental and Sustainable Eng Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05