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Multi-level Optimization and Applications with Non-Traditional Game Theory
Title
Multi-level Optimization and Applications with Non-Traditional Game Theory.
Creator
Yun, Guanxiang, Zheng, Qipeng, Boginski, Vladimir, Karwowski, Waldemar, Yong, Jiongmin, University of Central Florida
Abstract / Description
We study multi-level optimization problem on energy system, transportation system and information network. We use the concept of boundedly rational user equilibrium (BRUE) to predict the behaviour of users in systems. By using multi-level optimization method with BRUE, we can help to operate the system work in a more efficient way. Based on the introducing of model with BRUE constraints, it will lead to the uncertainty to the optimization model. We generate the robust optimization as the...
Show moreWe study multi-level optimization problem on energy system, transportation system and information network. We use the concept of boundedly rational user equilibrium (BRUE) to predict the behaviour of users in systems. By using multi-level optimization method with BRUE, we can help to operate the system work in a more efficient way. Based on the introducing of model with BRUE constraints, it will lead to the uncertainty to the optimization model. We generate the robust optimization as the multi-level optimization model to consider for the pessimistic condition with uncertainty. This dissertation mainly includes four projects. Three of them use the pricing strategy as the first level optimization decision variable. In general, our models' first level's decision variables are the measures that we can control, but the second level's decision variables are users behaviours that can only be restricted within BRUE with uncertainty.
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Date Issued
2019
Identifier
CFE0007881, ucf:52758
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0007881
EMERGENCY EVACUATION ROUTE PLANNING CONSIDERING HUMAN BEHAVIOR DURING SHORT- AND NO-NOTICE EMERGENCY SITUATIONS
Title
EMERGENCY EVACUATION ROUTE PLANNING CONSIDERING HUMAN BEHAVIOR DURING SHORT- AND NO-NOTICE EMERGENCY SITUATIONS.
Creator
Kittirattanapaiboon, Suebpong, Geiger, Christopher, University of Central Florida
Abstract / Description
Throughout United States and world history, disasters have caused not only significant loss of life, property but also enormous financial loss. The tsunami that occurred on December 26, 2004 is a telling example of the devastation that can occur unexpectedly. This unexpected natural event never happened before in this area. In addition, there was a lack of an emergency response plan for events of that magnitude. Therefore, this event resulted not only in a natural catastrophe for the people...
Show moreThroughout United States and world history, disasters have caused not only significant loss of life, property but also enormous financial loss. The tsunami that occurred on December 26, 2004 is a telling example of the devastation that can occur unexpectedly. This unexpected natural event never happened before in this area. In addition, there was a lack of an emergency response plan for events of that magnitude. Therefore, this event resulted not only in a natural catastrophe for the people of South and Southeast Asia, but it is also considered one of the greatest natural disasters in world history. After the giant wave dissipated, there were more than 230,000 people dead and more than US$10 billion in property damage and loss. Another significant event was the terrorist incident on September 11, 2001 (commonly referred to as 9/11) in United States. This event was unexpected and an unnatural, i.e., man-made event. It resulted in approximately 3,000 lives lost and about US$21 billion in property damage. These and other unexpected (or unanticipated) events give emergency management officials short- or no-notice to prevent or respond to the situation. These and other facts motivate the need for better emergency evacuation route planning (EERP) approaches in order to minimize the loss of human lives and property in short- or no-notice emergency situations. This research considers aspects of evacuation routing that have received little attention in research and, more importantly, in practice. Previous EERP models only either consider unidirectional evacuee flow from the source of a hazard to destinations of safety or unidirectional emergency first responder flow to the hazard source. However, in real-life emergency situations, these heterogeneous, incompatible flows occur simultaneously over a bi-directional capacitated lane-based travel network, especially in short- and no-notice emergencies. After presenting a review of the work related to the multiple flow EERP problem, mathematical formulations are presented for the EERP problem where the objective for each problem is to identify an evacuation routing plan (i.e., a traffic flow schedule) that maximizes evacuee and responder flow and minimizes network clearance time of both types of flow. In addition, we integrate the general human response behavior flow pattern, where the cumulative flow behavior follows different degrees of an S-shaped curve depending upon the level of the evacuation order. We extend the analysis to consider potential traffic flow conflicts between the two types of flow under these conditions. A conflict occurs when flow of different types occupy a roadway segment at the same time. Further, with different degrees of flow movement flow for both evacuee and responder flow, the identification of points of flow congestion on the roadway segments that occur within the transportation network is investigated.
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Date Issued
2009
Identifier
CFE0002645, ucf:48229
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0002645
THE APPLICATION OF "CRASHING" A PROJECT NETWORK TO SOLVE THE TIME/COST TRADEOFF IN RECAPITALIZATION OF THE UH-60A HELICOPTER
Title
THE APPLICATION OF "CRASHING" A PROJECT NETWORK TO SOLVE THE TIME/COST TRADEOFF IN RECAPITALIZATION OF THE UH-60A HELICOPTER.
Creator
Fortier, Gregory, Reilly, Charles, University of Central Florida
Abstract / Description
Since the beginning of project management, people have been asked to perform "more with less" in expeditious time while attempting to balance the inevitable challenge of the time/cost tradeoff. This is especially true within the Department of Defense today in prosecuting the Global War on Terrorism both in Afghanistan and Iraq. An unprecedented and consistent level of Operational Tempo has generated heavy demands on current equipment and has subsequently forced the need to recapitalize...
Show moreSince the beginning of project management, people have been asked to perform "more with less" in expeditious time while attempting to balance the inevitable challenge of the time/cost tradeoff. This is especially true within the Department of Defense today in prosecuting the Global War on Terrorism both in Afghanistan and Iraq. An unprecedented and consistent level of Operational Tempo has generated heavy demands on current equipment and has subsequently forced the need to recapitalize several legacy systems until suitable replacements can be implemented. This paper targets the UH-60A:A Recapitalization Program based at the Corpus Christi Army Depot in Corpus Christi, Texas. More specifically, we examine one of the nine existing project sub-networks within the UH-60A:A program, the structural/electrical upgrade phase. In crashing (i.e. adding manpower or labor hours) the network, we determine the minimal cost required to reduce the total completion time of the 68 activities within the network before a target completion time. A linear programming model is formulated and then solved for alternative scenarios. The first scenario is prescribed by the program manager and consists of simply hiring additional contractors to augment the existing personnel. The second and third scenarios consist of examining the effects of overtime, both in an aggressive situation (with limited longevity) and a more moderate situation (displaying greater sustainability over time). The initial linear programming model (Scenario 1) is crashed using estimates given from the program scheduler. The overtime models are crashed using reduced-time crash estimates. For Scenarios 2 and 3, the crashable times themselves are reduced by 50% and 75%, respectively. Initial results indicate that a completion time of 79.5 days is possible without crashing any activities in the network. The five-year historical average completion time is 156 days for this network. We continue to crash the network in each of the three scenarios and determine that the absolute shortest feasible completion times, 73 days for Scenario 1, 76 days for Scenario 2, and 77.5 days for Scenario 3. We further examine the models to observe similarities and differences in which activities get targeted for crashing and how that reduction affects the critical path of the network. These results suggests an in-depth study of using linear programming and applying it to project networks to grant project managers more critical insight that may help them better achieve their respective objectives. This work may also be useful as the groundwork for further refinement and application for maintenance managers conducting day-to-day unit level maintenance operations.
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Date Issued
2006
Identifier
CFE0001381, ucf:47008
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0001381
EVALUATING THE PERFORMANCE OF ANIMAL SHELTERS: AN APPLICATION OF DATA ENVELOPMENT ANALYSIS
Title
EVALUATING THE PERFORMANCE OF ANIMAL SHELTERS: AN APPLICATION OF DATA ENVELOPMENT ANALYSIS.
Creator
Heyde, Brandy, Reilly, Charles, University of Central Florida
Abstract / Description
The focus of this thesis is the application of data envelopment analysis to understand and evaluate the performance of diverse animal welfare organizations across the United States. The results include identification of the most efficient animal welfare organizations, at least among those that post statistics on their operations, and a discussion of various partnerships that may improve the performance of the more inefficient organizations. The Humane Society of the United States estimates...
Show moreThe focus of this thesis is the application of data envelopment analysis to understand and evaluate the performance of diverse animal welfare organizations across the United States. The results include identification of the most efficient animal welfare organizations, at least among those that post statistics on their operations, and a discussion of various partnerships that may improve the performance of the more inefficient organizations. The Humane Society of the United States estimates that there are 4000 - 6000 independently-run animal shelters across the United States, with an estimated 6-8 million companion animals entering them each year. Unfortunately, more than half of these animals are euthanized. The methods shared in this research illustrate how data envelopment analysis may help shelters improve these statistics through evaluation and cooperation. Data envelopment analysis (DEA) is based on the principle that the efficiency of an organization depends on its ability to transform its inputs into the desired outputs. The result of a DEA model is a single measure that summarizes the relative efficiency of each decision making unit (DMU) when compared with similar organizations. The DEA linear program defines an efficiency frontier with the most efficient animal shelters that are put into the model that "envelops" the other DMUs. Individual efficiency scores are calculated by determining how close each DMU is to reaching the frontier. The results shared in this research focus on the performance of 15 animal shelters. Lack of standardized data regarding individual animal shelter performance limited the ability to review a larger number of shelters and provide more robust results. Various programs are in place within the United States to improve the collection and availability of individual shelter performance. Specifically, the Asilomar Accords provide a strong framework for doing this and could significantly reduce euthanasia of companion animals if more shelters would adopt the practice of collecting and reporting their data in this format. It is demonstrated in this research that combining performance data with financial data within the data envelopment analysis technique can be powerful in helping shelters identify how to better deliver results. The addition of data from other organizations will make the results even more robust and useful for each shelter involved.
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Date Issued
2008
Identifier
CFE0002101, ucf:47557
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0002101
Systems Analysis for Urban Water Infrastructure Expansion with Global Change Impact under Uncertainties
Title
Systems Analysis for Urban Water Infrastructure Expansion with Global Change Impact under Uncertainties.
Creator
Qi, Cheng, Chang, Ni-bin, Geiger, Christopher, Xanthopoulos, Petros, Wanielista, Martin, University of Central Florida
Abstract / Description
Over the past decades, cost-effectiveness principle or cost-benefit analysis has been employed oftentimes as a typical assessment tool for the expansion of drinking water utility. With changing public awareness of the inherent linkages between climate change, population growth and economic development, the addition of global change impact in the assessment regime has altered the landscape of traditional evaluation matrix. Nowadays, urban drinking water infrastructure requires careful long...
Show moreOver the past decades, cost-effectiveness principle or cost-benefit analysis has been employed oftentimes as a typical assessment tool for the expansion of drinking water utility. With changing public awareness of the inherent linkages between climate change, population growth and economic development, the addition of global change impact in the assessment regime has altered the landscape of traditional evaluation matrix. Nowadays, urban drinking water infrastructure requires careful long-term expansion planning to reduce the risk from global change impact with respect to greenhouse gas (GHG) emissions, economic boom and recession, as well as water demand variation associated with population growth and migration. Meanwhile, accurate prediction of municipal water demand is critically important to water utility in a fast growing urban region for the purpose of drinking water system planning, design and water utility asset management. A system analysis under global change impact due to the population dynamics, water resources conservation, and environmental management policies should be carried out to search for sustainable solutions temporally and spatially with different scales under uncertainties. This study is aimed to develop an innovative, interdisciplinary, and insightful modeling framework to deal with global change issues as a whole based on a real-world drinking water infrastructure system expansion program in Manatee County, Florida. Four intertwined components within the drinking water infrastructure system planning were investigated and integrated, which consists of water demand analysis, GHG emission potential, system optimization for infrastructure expansion, and nested minimax-regret (NMMR) decision analysis under uncertainties. In the water demand analysis, a new system dynamics model was developed to reflect the intrinsic relationship between water demand and changing socioeconomic environment. This system dynamics model is based on a coupled modeling structure that takes the interactions among economic and social dimensions into account offering a satisfactory platform. In the evaluation of GHG emission potential, a life cycle assessment (LCA) is conducted to estimate the carbon footprint for all expansion alternatives for water supply. The result of this LCA study provides an extra dimension for decision makers to extract more effective adaptation strategies. Both water demand forecasting and GHG emission potential were deemed as the input information for system optimization when all alternatives are taken into account simultaneously. In the system optimization for infrastructure expansion, a multiobjective optimization model was formulated for providing the multitemporal optimal facility expansion strategies. With the aid of a multi-stage planning methodology over the partitioned time horizon, such a systems analysis has resulted in a full-scale screening and sequencing with respect to multiple competing objectives across a suite of management strategies. In the decision analysis under uncertainty, such a system optimization model was further developed as a unique NMMR programming model due to the uncertainties imposed by the real-world problem. The proposed NMMR algorithm was successfully applied for solving the real-world problem with a limited scale for the purpose of demonstration.
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Date Issued
2012
Identifier
CFE0004425, ucf:49354
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0004425
A Comparative Evaluation of FDSA,GA, and SA Non-Linear Programming Algorithms and Development of System-Optimal Dynamic Congestion Pricing Methodology on I-95 Express
Title
A Comparative Evaluation of FDSA,GA, and SA Non-Linear Programming Algorithms and Development of System-Optimal Dynamic Congestion Pricing Methodology on I-95 Express.
Creator
Graham, Don, Radwan, Ahmed, Abdel-Aty, Mohamed, Al-Deek, Haitham, Uddin, Nizam, University of Central Florida
Abstract / Description
As urban population across the globe increases, the demand for adequatetransportation grows. Several strategies have been suggested as a solution to the congestion which results from this high demand outpacing the existing supply of transportation facilities.High (-)Occupancy Toll (HOT) lanes have become increasingly more popular as a feature on today's highway system. The I-95 Express HOT lane in Miami Florida, which is currently being expanded from a single Phase (Phase I) into two Phases,...
Show moreAs urban population across the globe increases, the demand for adequatetransportation grows. Several strategies have been suggested as a solution to the congestion which results from this high demand outpacing the existing supply of transportation facilities.High (-)Occupancy Toll (HOT) lanes have become increasingly more popular as a feature on today's highway system. The I-95 Express HOT lane in Miami Florida, which is currently being expanded from a single Phase (Phase I) into two Phases, is one such HOT facility. With the growing abundance of such facilities comes the need for in- depth study of demand patterns and development of an appropriate pricing scheme which reduces congestion.This research develops a method for dynamic pricing on the I-95 HOT facility such as to minimize total travel time and reduce congestion. We apply non-linear programming (NLP) techniques and the finite difference stochastic approximation (FDSA), genetic algorithm (GA) and simulated annealing (SA) stochastic algorithms to formulate and solve the problem within a cell transmission framework. The solution produced is the optimal flow and optimal toll required to minimize total travel time and thus is the system-optimal solution.We perform a comparative evaluation of FDSA, GA and SA non-linear programmingalgorithms used to solve the NLP and the ANOVA results show that there are differences in the performance of the NLP algorithms in solving this problem and reducing travel time. We then conclude by demonstrating that econometric forecasting methods utilizing vector autoregressive (VAR) techniques can be applied to successfully forecast demand for Phase 2 of the 95 Express which is planned for 2014.
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Date Issued
2013
Identifier
CFE0005000, ucf:50019
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0005000