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META-RAPS: PARAMETER SETTING AND NEW APPLICATIONS
Title
META-RAPS: PARAMETER SETTING AND NEW APPLICATIONS.
Creator
Hepdogan, Seyhun, Whitehouse, Gary, University of Central Florida
Abstract / Description
ABSTRACT Recently meta-heuristics have become a popular solution methodology, in terms of both research and application, for solving combinatorial optimization problems. Meta-heuristic methods guide simple heuristics or priority rules designed to solve a particular problem. Meta-heuristics enhance these simple heuristics by using a higher level strategy. The advantage of using meta-heuristics over conventional optimization methods is meta-heuristics are able to find good (near optimal)...
Show moreABSTRACT Recently meta-heuristics have become a popular solution methodology, in terms of both research and application, for solving combinatorial optimization problems. Meta-heuristic methods guide simple heuristics or priority rules designed to solve a particular problem. Meta-heuristics enhance these simple heuristics by using a higher level strategy. The advantage of using meta-heuristics over conventional optimization methods is meta-heuristics are able to find good (near optimal) solutions within a reasonable computation time. Investigating this line of research is justified because in most practical cases with medium to large scale problems, the use of meta-heuristics is necessary to be able to find a solution in a reasonable time. The specific meta-heuristic studied in this research is, Meta-RaPS; Meta-heuristic for Randomized Priority Search which is developed by DePuy and Whitehouse in 2001. Meta-RaPS is a generic, high level strategy used to modify greedy algorithms based on the insertion of a random element (Moraga, 2002). To date, Meta-RaPS had been applied to different types of combinatorial optimization problems and achieved comparable solution performance to other meta-heuristic techniques. The specific problem studied in this dissertation is parameter setting of Meta-RaPS. The topic of parameter setting for meta-heuristics has not been extensively studied in the literature. Although the parameter setting method devised in this dissertation is used primarily on Meta-RaPS, it is applicable to any meta-heuristic's parameter setting problem. This dissertation not only enhances the power of Meta-RaPS by parameter tuning but also it introduces a robust parameter selection technique with wide-spread utility for many meta-heuristics. Because the distribution of solution values generated by meta-heuristics for combinatorial optimization problems is not normal, the current parameter setting techniques which employ a parametric approach based on the assumption of normality may not be appropriate. The proposed method is Non-parametric Based Genetic Algorithms. Based on statistical tests, the Non-parametric Based Genetic Algorithms (NPGA) is able to enhance the solution quality of Meta-RaPS more than any other parameter setting procedures benchmarked in this research. NPGA sets the best parameter settings, of all the methods studied, for 38 of the 41 Early/Tardy Single Machine Scheduling with Common Due Date and Sequence-Dependent Setup Time (ETP) problems and 50 of the 54 0-1 Multidimensional Knapsack Problems (0-1 MKP). In addition to the parameter setting procedure discussed, this dissertation provides two Meta-RaPS combinatorial optimization problem applications, the 0-1 MKP, and the ETP. For the ETP problem, the Meta-RaPS application in this dissertation currently gives the best meta-heuristic solution performance so far in the literature for common ETP test sets. For the large ETP test set, Meta-RaPS provided better solution performance than Simulated Annealing (SA) for 55 of the 60 problems. For the small test set, in all four different small problem sets, the Meta-RaPS solution performance outperformed exiting algorithms in terms of average percent deviation from the optimal solution value. For the 0-1 MKP, the present Meta-RaPS application performs better than the earlier Meta-RaPS applications by other researchers on this problem. The Meta-RaPS 0-1 MKP application presented here has better solution quality than the existing Meta-RaPS application (Moraga, 2005) found in the literature. Meta-RaPS gives 0.75% average percent deviation, from the best known solutions, for the 270 0-1 MKP test problems.
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Date Issued
2006
Identifier
CFE0001206, ucf:46949
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0001206
CLASSROOM MATHEMATICAL PRACTICES IN A PRESERVICE ELEMENTARY MATHEMATICS EDUCATION COURSE USING AN INSTRUCTIONAL SEQUENCE RELATED TO PLACE VALUE AND OPERATIONS
Title
CLASSROOM MATHEMATICAL PRACTICES IN A PRESERVICE ELEMENTARY MATHEMATICS EDUCATION COURSE USING AN INSTRUCTIONAL SEQUENCE RELATED TO PLACE VALUE AND OPERATIONS.
Creator
Andreasen, Janet, Dixon, Juli, University of Central Florida
Abstract / Description
This qualitative study documents a classroom teaching experiment in a semester-long undergraduate mathematics education course for 16 prospective elementary school teachers. The purpose of this study was to investigate how social aspects of the classroom environment facilitated the collective mathematical learning of place value and whole number operations by preservice elementary school teachers. Design-based research methodology was used for formulating the study. A hypothetical learning...
Show moreThis qualitative study documents a classroom teaching experiment in a semester-long undergraduate mathematics education course for 16 prospective elementary school teachers. The purpose of this study was to investigate how social aspects of the classroom environment facilitated the collective mathematical learning of place value and whole number operations by preservice elementary school teachers. Design-based research methodology was used for formulating the study. A hypothetical learning trajectory and instructional sequence related to place value and operations were created and refined in the two semesters prior to this study. The instructional sequence was in its third iteration for this study. The developmental levels that children progress through in learning place value and operations were used in identifying the learning trajectory and supporting tasks in which the preservice teachers were asked to engage. A large portion of the instructional sequence involved a setting of base eight instead of base ten. The sequence returned to base ten in order to discuss whole number operations and alternative strategies for operations in an effort to further develop the preservice teachers' conceptual understandings of place value and operations and to examine children's thinking strategies. Data were collected through video-taped recordings of class sessions, audio-taped recordings of table discussions and research team meetings, field notes, and journals written by the research team. Sixteen preservice teachers participated in the study which lasted over 5 class sessions of 3 hours and 10 minutes each. The emergent perspective which attempts to coordinate the individual learning and the social aspects of the classroom that support collective learning was used as an interpretive lens for data collection and analysis. The social aspects along with some aspects of individual student understandings together give an indication of collective mathematical understandings of the students as a whole group. Social norms established were: a) the expectation of providing explanations and justifications for solutions and solution methods, b) making sense of each other's solutions and c) asking questions of classmates or the instructor. Sociomathematical norms that were valued but not fully established were: a) criteria for different solutions and solution methods and b) criteria for what constituted a good explanation. Data analysis for the establishment of classroom mathematical practices was conducted using Toulmin's argumentation model (Toulmin, 1969). A three phase approach described by Rasmussen and Stephan (in press) was used in determining what constituted a classroom mathematical practice. The classroom mathematical practices that facilitated student learning in this study were: a) unitizing, b) flexibly representing numbers, and c) reasoning about operations. This study led to the refinement of the hypothetical learning trajectory and further progress in defining an instructional theory of how preservice teachers may come to understand place value and whole number operations.
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Date Issued
2006
Identifier
CFE0000917, ucf:46718
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0000917
Modeling and Solving Large-scale Stochastic Mixed-Integer Problems in Transportation and Power Systems
Title
Modeling and Solving Large-scale Stochastic Mixed-Integer Problems in Transportation and Power Systems.
Creator
Huang, Zhouchun, Zheng, Qipeng, Xanthopoulos, Petros, Pazour, Jennifer, Chang, Ni-bin, University of Central Florida
Abstract / Description
In this dissertation, various optimization problems from the area of transportation and power systems will be respectively investigated and the uncertainty will be considered in each problem. Specifically, a long-term problem of electricity infrastructure investment is studied to address the planning for capacity expansion in electrical power systems with the integration of short-term operations. The future investment costs and real-time customer demands cannot be perfectly forecasted and...
Show moreIn this dissertation, various optimization problems from the area of transportation and power systems will be respectively investigated and the uncertainty will be considered in each problem. Specifically, a long-term problem of electricity infrastructure investment is studied to address the planning for capacity expansion in electrical power systems with the integration of short-term operations. The future investment costs and real-time customer demands cannot be perfectly forecasted and thus are considered to be random. Another maintenance scheduling problem is studied for power systems, particularly for natural gas fueled power plants, taking into account gas contracting and the opportunity of purchasing and selling gas in the spot market as well as the maintenance scheduling considering the uncertainty of electricity and gas prices in the spot market. In addition, different vehicle routing problems are researched seeking the route for each vehicle so that the total traveling cost is minimized subject to the constraints and uncertain parameters in corresponding transportation systems.The investigation of each problem in this dissertation mainly consists of two parts, i.e., the formulation of its mathematical model and the development of solution algorithm for solving the model. The stochastic programming is applied as the framework to model each problem and address the uncertainty, while the approach of dealing with the randomness varies in terms of the relationships between the uncertain elements and objective functions or constraints. All the problems will be modeled as stochastic mixed-integer programs, and the huge numbers of involved decision variables and constraints make each problem large-scale and very difficult to manage. In this dissertation, efficient algorithms are developed for these problems in the context of advanced methodologies of optimization and operations research, such as branch and cut, benders decomposition, column generation and Lagrangian method. Computational experiments are implemented for each problem and the results will be present and discussed. The research carried out in this dissertation would be beneficial to both researchers and practitioners seeking to model and solve similar optimization problems in transportation and power systems when uncertainty is involved.
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Date Issued
2016
Identifier
CFE0006328, ucf:51559
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0006328
A real-time crane service scheduling decision support system (CSS-DSS) for construction tower cranes
Title
A real-time crane service scheduling decision support system (CSS-DSS) for construction tower cranes.
Creator
Zavichi Tork, Amir, Madani Larijani, Kaveh, Oloufa, Amr, Tatari, Mehmet, Xanthopoulos, Petros, University of Central Florida
Abstract / Description
The success of construction projects depends on proper use of construction equipment and machinery to a great extent. Thus, appropriate planning and control of the activities that rely on construction equipment could have significant effects on improving the efficiency of project operations. Cranes are the largest and most conspicuous construction equipment, widely used in typical construction sites. They play a major role in relocation of materials in horizontal and vertical directions on...
Show moreThe success of construction projects depends on proper use of construction equipment and machinery to a great extent. Thus, appropriate planning and control of the activities that rely on construction equipment could have significant effects on improving the efficiency of project operations. Cranes are the largest and most conspicuous construction equipment, widely used in typical construction sites. They play a major role in relocation of materials in horizontal and vertical directions on construction sites. Given the nature of activities relying on construction cranes in various stages of a project, cranes normally have control over the critical path of the project with the potential to create schedule bottlenecks and delaying the completion of the project. This dissertation intends to improve crane operations efficiency by developing a new framework for optimizing crane service sequence schedule. The crane service sequence problem is mathematically formulated as an NP-complete optimization problem based on the well-known Travel Salesman Problem (TSP) and is solved using different optimization techniques depending on the problem's size and complexity. The proposed framework sets the basis for developing near-real time decision support tools for on-site optimization of crane operations sequence. To underline the value of the proposed crane sequence optimization methods, these methods are employed to solve several numerical examples. Results show that the proposed method can create a travel time saving of 28% on average in comparison with conventional scheduling methods such as First in First out (FIFO), Shortest Job First (SJF), and Earliest Deadline First (EDF).
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Date Issued
2013
Identifier
CFE0005078, ucf:50738
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0005078
AN ACTION RESEARCH STUDY INVOLVING FIFTH-GRADE STUDENTS LEARNING FRACTIONS THROUGH A SITUATIVE PERSPECTIVE WITH STORY PROBLEMS
Title
AN ACTION RESEARCH STUDY INVOLVING FIFTH-GRADE STUDENTS LEARNING FRACTIONS THROUGH A SITUATIVE PERSPECTIVE WITH STORY PROBLEMS.
Creator
Allen, Colleen, Dixon, Juli, University of Central Florida
Abstract / Description
ABSTRACT The purpose of this action research study was to investigate the affects of teaching through a situative perspective with story problems on students' understanding of fraction concepts and operations in my fifth-grade mathematics classroom. Students participated in twelve weeks of instruction. Data was collected in the form of pre and post tests, audiotaped and videotaped recordings of instructional sessions, and student work samples. Data analysis revealed that my students...
Show moreABSTRACT The purpose of this action research study was to investigate the affects of teaching through a situative perspective with story problems on students' understanding of fraction concepts and operations in my fifth-grade mathematics classroom. Students participated in twelve weeks of instruction. Data was collected in the form of pre and post tests, audiotaped and videotaped recordings of instructional sessions, and student work samples. Data analysis revealed that my students constructed their own knowledge about various fraction concepts and operations because students engaged in discussions, after solving story problems, that developed, extended and restructured their knowledge. One example of this occurred after students had solved an equal-sharing problem. Two students came up with different answers and another student explained why both answers were equivalent. Student work samples and post test results indicated that the one student's explanation was understood, adopted and extended by all the students in my class. The data also revealed that students' pictures typically represented the context and action of the story problems. For example, subtraction problems dealing with length were usually represented by number lines or horizontal rectangles with crossed-out markings to show the subtraction operation. Throughout this research study, I discovered that my students were capable of learning from each other and solving problems for which they have no preconceived algorithm. I also learned that analyzing students' work and listening to their discussions in ways that focused on their thinking, not their answers, provided me with information about what my students were grasping and not grasping.
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Date Issued
2005
Identifier
CFE0000538, ucf:46423
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0000538
IMPROVING AIRLINE SCHEDULE RELIABILITY USING A STRATEGIC MULTI-OBJECTIVE RUNWAY SLOT ASSIGNMENT SEARCH HEURISTIC
Title
IMPROVING AIRLINE SCHEDULE RELIABILITY USING A STRATEGIC MULTI-OBJECTIVE RUNWAY SLOT ASSIGNMENT SEARCH HEURISTIC.
Creator
Hafner, Florian, Sepulveda, Alejandro, University of Central Florida
Abstract / Description
Improving the predictability of airline schedules in the National Airspace System (NAS) has been a constant endeavor, particularly as system delays grow with ever-increasing demand. Airline schedules need to be resistant to perturbations in the system including Ground Delay Programs (GDPs) and inclement weather. The strategic search heuristic proposed in this dissertation significantly improves airline schedule reliability by assigning airport departure and arrival slots to each flight in the...
Show moreImproving the predictability of airline schedules in the National Airspace System (NAS) has been a constant endeavor, particularly as system delays grow with ever-increasing demand. Airline schedules need to be resistant to perturbations in the system including Ground Delay Programs (GDPs) and inclement weather. The strategic search heuristic proposed in this dissertation significantly improves airline schedule reliability by assigning airport departure and arrival slots to each flight in the schedule across a network of airports. This is performed using a multi-objective optimization approach that is primarily based on historical flight and taxi times but also includes certain airline, airport, and FAA priorities. The intent of this algorithm is to produce a more reliable, robust schedule that operates in today's environment as well as tomorrow's 4-Dimensional Trajectory Controlled system as described the FAA's Next Generation ATM system (NextGen). This novel airline schedule optimization approach is implemented using a multi-objective evolutionary algorithm which is capable of incorporating limited airport capacities. The core of the fitness function is an extensive database of historic operating times for flight and ground operations collected over a two year period based on ASDI and BTS data. Empirical distributions based on this data reflect the probability that flights encounter various flight and taxi times. The fitness function also adds the ability to define priorities for certain flights based on aircraft size, flight time, and airline usage. The algorithm is applied to airline schedules for two primary US airports: Chicago O'Hare and Atlanta Hartsfield-Jackson. The effects of this multi-objective schedule optimization are evaluated in a variety of scenarios including periods of high, medium, and low demand. The schedules generated by the optimization algorithm were evaluated using a simple queuing simulation model implemented in AnyLogic. The scenarios were simulated in AnyLogic using two basic setups: (1) using modes of flight and taxi times that reflect highly predictable 4-Dimensional Trajectory Control operations and (2) using full distributions of flight and taxi times reflecting current day operations. The simulation analysis showed significant improvements in reliability as measured by the mean square difference (MSD) of filed versus simulated flight arrival and departure times. Arrivals showed the most consistent improvements of up to 80% in on-time performance (OTP). Departures showed reduced overall improvements, particularly when the optimization was performed without the consideration of airport capacity. The 4-Dimensional Trajectory Control environment more than doubled the on-time performance of departures over the current day, more chaotic scenarios. This research shows that airline schedule reliability can be significantly improved over a network of airports using historical flight and taxi time data. It also provides for a mechanism to prioritize flights based on various airline, airport, and ATC goals. The algorithm is shown to work in today's environment as well as tomorrow's NextGen 4-Dimensional Trajectory Control setup.
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Date Issued
2008
Identifier
CFE0002067, ucf:47572
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0002067
BRAVE NEW WORLD RELOADED: ADVOCATING FOR BASIC CONSTITUTIONAL SEARCH PROTECTIONS TO APPLY TO CELL PHONES FROM EAVESDROPPING AND TRACKING BY THE GOVERNMENT AND CORPORATE ENTITIES
Title
BRAVE NEW WORLD RELOADED: ADVOCATING FOR BASIC CONSTITUTIONAL SEARCH PROTECTIONS TO APPLY TO CELL PHONES FROM EAVESDROPPING AND TRACKING BY THE GOVERNMENT AND CORPORATE ENTITIES.
Creator
Berrios-Ayala, Mark, Milon, Abby, University of Central Florida
Abstract / Description
Imagine a world where someone's personal information is constantly compromised, where federal government entities AKA Big Brother always knows what anyone is Googling, who an individual is texting, and their emoticons on Twitter. Government entities have been doing this for years; they never cared if they were breaking the law or their moral compass of human dignity. Every day the Federal government blatantly siphons data with programs from the original ECHELON to the new series like PRISM...
Show moreImagine a world where someone's personal information is constantly compromised, where federal government entities AKA Big Brother always knows what anyone is Googling, who an individual is texting, and their emoticons on Twitter. Government entities have been doing this for years; they never cared if they were breaking the law or their moral compass of human dignity. Every day the Federal government blatantly siphons data with programs from the original ECHELON to the new series like PRISM and Xkeyscore so they can keep their tabs on issues that are none of their business; namely, the personal lives of millions. Our allies are taking note; some are learning our bad habits, from Government Communications Headquarters' (GCHQ) mass shadowing sharing plan to America's Russian inspiration, SORM. Some countries are following the United States' poster child pose of a Brave New World like order of global events. Others like Germany are showing their resolve in their disdain for the rise of tyranny. Soon, these new found surveillance troubles will test the resolve of the American Constitution and its nation's strong love and tradition of liberty. Courts are currently at work to resolve how current concepts of liberty and privacy apply to the current conditions facing the privacy of society. It remains to be determined how liberty will be affected as well; liberty for the United States of America, for the European Union, the Russian Federation and for the people of the World in regards to the extent of privacy in today's blurred privacy expectations.
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Date Issued
2014
Identifier
CFH0004537, ucf:45187
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFH0004537