Engineering Commons^™

Exploiting Symmetry In Linear And Integer Linear Programming, Ethan Jedidiah Deakins

Doctoral Dissertations

This thesis explores two algorithmic approaches for exploiting symmetries in linear and integer linear programs. The first is orbital crossover, a novel method of crossover designed to exploit symmetry in linear programs. Symmetry has long been considered a curse in combinatorial optimization problems, but significant progress has been made. Up until recently, symmetry exploitation in linear programs was not worth the upfront cost of symmetry detection. However, recent results involving a generalization of symmetries, equitable partitions, has made the upfront cost much more manageable.

The motivation for orbital crossover is that many highly symmetric integer linear programs exist, and …

Enhanced Load Balancing Based On Hybrid Artificial Bee Colony With Enhanced Β-Hill Climbing In Cloud, Maha Zeedan, Gamal Attiya, Nawal El-Fishawy

Mansoura Engineering Journal

This paper proposes enhanced load balancer based artificial bee colony and β-Hill climbing for improving the performance metrics such as response time, processing cost, and utilization to avoid overloaded or under loaded situations of virtual machines. In this study, the suggested load balancer is called enhanced load balancing based on hybrid artificial bee colony with enhanced β-Hill climbing (ELBABCEβHC) to improve the response time, processing cost and the resource utilization. Our proposed approach starts by ranking the task then the greedy randomized adaptive search procedure (GRASP) is used in initializing populations. Further, the binary artificial bee colony (BABC) enhanced with …

Comparative Analysis Of Fullstack Development Technologies: Frontend, Backend And Database, Qozeem Odeniran

Electronic Theses and Dissertations

Accessing websites with various devices has brought changes in the field of application development. The choice of cross-platform, reusable frameworks is very crucial in this era. This thesis embarks in the evaluation of front-end, back-end, and database technologies to address the status quo. Study-a explores front-end development, focusing on angular.js and react.js. Using these frameworks, comparative web applications were created and evaluated locally. Important insights were obtained through benchmark tests, lighthouse metrics, and architectural evaluations. React.js proves to be a performance leader in spite of the possible influence of a virtual machine, opening the door for additional research. Study b …

Machine Learning In Requirements Elicitation: A Literature Review, Cheligeer Cheligeer, Jingwei Huang, Guosong Wu, Nadia Bhuiyan, Yuan Xu, Yong Zeng

Engineering Management & Systems Engineering Faculty Publications

A growing trend in requirements elicitation is the use of machine learning (ML) techniques to automate the cumbersome requirement handling process. This literature review summarizes and analyzes studies that incorporate ML and natural language processing (NLP) into demand elicitation. We answer the following research questions: (1) What requirement elicitation activities are supported by ML? (2) What data sources are used to build ML-based requirement solutions? (3) What technologies, algorithms, and tools are used to build ML-based requirement elicitation? (4) How to construct an ML-based requirements elicitation method? (5) What are the available tools to support ML-based requirements elicitation methodology? Keywords …

Disaster Damage Categorization Applying Satellite Images And Machine Learning Algorithm, Farinaz Sabz Ali Pour, Adrian Gheorghe

Engineering Management & Systems Engineering Faculty Publications

Special information has a significant role in disaster management. Land cover mapping can detect short- and long-term changes and monitor the vulnerable habitats. It is an effective evaluation to be included in the disaster management system to protect the conservation areas. The critical visual and statistical information presented to the decision-makers can help in mitigation or adaption before crossing a threshold. This paper aims to contribute in the academic and the practice aspects by offering a potential solution to enhance the disaster data source effectiveness. The key research question that the authors try to answer in this paper is how …

An Integrated Approach For Remanufacturing Job Shop Scheduling With Routing Alternatives., Ling Ling Li, Cong Bo Li, Li Li, Ying Tang, Qing Shan Yang

Henry M. Rowan College of Engineering Faculty Scholarship

Remanufacturing is a practice of growing importance due to increasing environmental awareness and regulations. However, the stochastic natures inherent in the remanufacturing processes complicate its scheduling. This paper undertakes the challenge and presents a remanufacturing job shop scheduling approach by integrating alternative routing assignment and machine resource dispatching. A colored timed Petri net is introduced to model the dynamics of remanufacturing process, such as various process routings, uncertain operation times for cores, and machine resource conflicts. With the color attributes in Petri nets, two types of decision points, recovery routing selection and resource dispatching, are introduced and linked with places …

The Role Of Artificial Intelligence In Business Decision Making, Chase Rainwater

Operations Management Presentations

When we think of artificial intelligence, we often are drawn to the self-driving cars, voice-based home technologies and automated online interactions that fill the news and drive our daily activities. However, the root of these advancements, machine learning, is a predictive analytics technique that has much broader applicability. With the age of “big data” and the buzz around “data science” continuing to grow, decision-makers are asking themselves if emerging technologies, such as machine learning, can help improve business processes.

In this seminar we will demystify the fundamental concepts that comprise machine learning. The differences between supervised and unsupervised learning, as …

A Mathematical Framework On Machine Learning: Theory And Application, Bin Shi

FIU Electronic Theses and Dissertations

The dissertation addresses the research topics of machine learning outlined below. We developed the theory about traditional first-order algorithms from convex opti- mization and provide new insights in nonconvex objective functions from machine learning. Based on the theory analysis, we designed and developed new algorithms to overcome the difficulty of nonconvex objective and to accelerate the speed to obtain the desired result. In this thesis, we answer the two questions: (1) How to design a step size for gradient descent with random initialization? (2) Can we accelerate the current convex optimization algorithms and improve them into nonconvex objective? For application, …

A Selective-Discrete Particle Swarm Optimization Algorithm For Solving A Class Of Orienteering Problems, Aldy Gunawan, Vincent F. Yu, Perwira Redi, Parida Jewpanya, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

This study addresses a class of NP-hard problem called the Orienteering Problem (OP), which belongs to a well-known class of vehicle routing problems. In the OP, a set of nodes that associated with a location and a score is given. The time required to travel between each pair of nodes is known in advance. The total travel time is limited by a predetermined time budget. The objective is to select a subset of nodes to be visited that maximizes the total collected score within a path. The Team OP (TOP) is an extension of OP that incorporates multiple paths. Another …

Optimizing Macd Parameters Via Genetic Algorithms For Soybean Futures, Phoebe S. Wiles, David Lee Enke

Engineering Management and Systems Engineering Faculty Research & Creative Works

To create profits, traders must time the market correctly and enter and exit positions at ideal times. Finding the optimal time to enter the market can be quite daunting. The soybean market can be volatile and complex. Weather, sentiment, supply, and demand can all affect the price of soybeans. Traders typically use either fundamental analysis or technical analysis to predict the market for soybean futures' contracts. Every agricultural future's contract or security contract is different in its nature, volatility, and structure. Therefore, the purpose of this research is to optimize the moving average convergence divergence parameter values from traditionally used …

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

Research Collection School Of Computing and Information Systems

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

A Computational Intelligence Approach To System-Of-Systems Architecting Incorporating Multi-Objective Optimization, David M. Curry, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

A computational intelligence approach to system-of-systems architecting is developed using multi-objective optimization. Such an approach yields a set of optimal solutions (the Pareto set) which has both advantages and disadvantages. The primary benefit is that a set of solutions provides a picture of the optimal solution space that a single solution cannot. The primary difficulty is making use of a potentially infinite set of solutions. Therefore, a significant part of this approach is the development of a method to model the solution set with a finite number of points allowing the architect to intelligently choose a subset of optimal solutions …

Scheduling And Resource Allocation In Wireless Sensor Networks, Yosef Alayev

Dissertations, Theses, and Capstone Projects

In computer science and telecommunications, wireless sensor networks are an active research area. Each sensor in a wireless sensor network has some pre-defined or on demand tasks such as collecting or disseminating data. Network resources, such as broadcast channels, number of sensors, power, battery life, etc., are limited. Hence, a schedule is required to optimally allocate network resources so as to maximize some profit or minimize some cost. This thesis focuses on scheduling problems in the wireless sensor networks environment. In particular, we study three scheduling problems in the wireless sensor networks: broadcast scheduling, sensor scheduling for area monitoring, and …

Data Mining Based Hybridization Of Meta-Raps, Fatemah Al-Duoli, Ghaith Rabadi

Engineering Management & Systems Engineering Faculty Publications

Though metaheuristics have been frequently employed to improve the performance of data mining algorithms, the opposite is not true. This paper discusses the process of employing a data mining algorithm to improve the performance of a metaheuristic algorithm. The targeted algorithms to be hybridized are the Meta-heuristic for Randomized Priority Search (Meta-RaPS) and an algorithm used to create an Inductive Decision Tree. This hybridization focuses on using a decision tree to perform on-line tuning of the parameters in Meta-RaPS. The process makes use of the information collected during the iterative construction and improvement phases Meta-RaPS performs. The data mining algorithm …

Tesla: An Energy-Saving Agent That Leverages Schedule Flexibility, Jun Young Kwak, Pradeep Varakantham, Rajiv Maheswaran, Burcin Becerik-Gerber, Milind Tambe

Research Collection School Of Computing and Information Systems

This innovative application paper presents TESLA, an agent-based application for optimizing the energy use in commercial buildings. TESLA’s key insight is that adding flexibility to event/meeting schedules can lead to significant energy savings. TESLA provides three key contributions: (i) three online scheduling algorithms that consider flexibility of people’s preferences for energyefficient scheduling of incrementally/dynamically arriving meetings and events; (ii) an algorithm to effectively identify key meetings that lead to significant energy savings by adjusting their flexibility; and (iii) surveys of real users that indicate that TESLA’s assumptions exist in practice. TESLA was evaluated on data of over 110,000 meetings held …

Adaptive Decision Support For Structured Organizations: A Case For Orgpomdps, Pradeep Reddy Varakantham, Nathan Schurr, Alan Carlin, Christopher Amato

Research Collection School Of Computing and Information Systems

In today's world, organizations are faced with increasingly large and complex problems that require decision-making under uncertainty. Current methods for optimizing such decisions fall short of handling the problem scale and time constraints. We argue that this is due to existing methods not exploiting the inherent structure of the organizations which solve these problems. We propose a new model called the OrgPOMDP (Organizational POMDP), which is based on the partially observable Markov decision process (POMDP). This new model combines two powerful representations for modeling large scale problems: hierarchical modeling and factored representations. In this paper we make three key contributions: …

Multi-Objective Optimization Of Mixed-Variable, Stochastic Systems Using Single-Objective Formulations, Todd J. Paciencia

Theses and Dissertations

Many problems exist where one desires to optimize systems with multiple, often competing, objectives. Further, these problems may not have a closed form representation, and may also have stochastic responses. Recently, a method expanded mixed variable generalized pattern search/ranking and selection (MVPS-RS) and Mesh Adaptive Direct Search (MADS) developed for single-objective, stochastic problems to the multi-objective case by using aspiration and reservation levels. However, the success of this method in approximating the true Pareto solution set can be dependent upon several factors. These factors include the experimental design and ranges of the aspiration and reservation levels, and the approximation quality …

Search Techniques For Multi-Objective Optimization Of Mixed Variable Systems Having Stochastic Responses, Jennifer G. Walston

Theses and Dissertations

A research approach is presented for solving stochastic, multi-objective optimization problems. First, the class of mesh adaptive direct search (MADS) algorithms for nonlinearly constrained optimization is extended to mixed variable problems. The resulting algorithm, MV-MADS, is then extended to stochastic problems (MVMADS-RS), via a ranking and selection procedure. Finally, a two-stage method is developed that combines the generalized pattern search/ranking and selection (MGPS-RS) algorithms for single-objective, mixed variable, stochastic problems with a multi-objective approach that makes use of interactive techniques for the specification of aspiration and reservation levels, scalarization functions, and multi-objective ranking and selection. A convergence analysis for the …

Optimization Of A Multi-Echelon Repair System Via Generalized Pattern Search With Ranking And Selection: A Computational Study, Derek D. Tharaldson

Theses and Dissertations

With increasing developments in computer technology and available software, simulation is becoming a widely used tool to model, analyze, and improve a real world system or process. However, simulation in itself is not an optimization approach. Common optimization procedures require either an explicit mathematical formulation or numerous function evaluations at improving iterative points. Mathematical formulation is generally impossible for problems where simulation is relevant, which are characteristically the types of problems that arise in practical applications. Further complicating matters is the variability in the simulation response which can cause problems in iterative techniques using the simulation model as a function …

Including Organizational Cultural Parameters In Work Processes, Holly A. H. Handley, Nancy J. Heacox

Engineering Management & Systems Engineering Faculty Publications

Recent work in modeling decision-making work processes has focused on including the national culture of individual decision-makers in order to emphasize the differences in decision criteria between decision-makers of different nationalities. In addition to nationality, a decision-maker is also a member of an organization and brings this organizational culture to his role in the work process, where it may also affect his task performance. In order to represent the organizational impact on the work process, five organizational cultural parameters were identified and included in an algorithm for modeling and simulation of cultural difference in human decision-making. While the five modifiers …

An Approach For Tasking Allocated Combat Resources To Targets, David A. Koewler

Theses and Dissertations

Tasking allocated combat aircraft to strike targets is a complicated and time-consuming process for combat planners. Currently, the process of scheduling missions is a two to four day process. To be able to respond quickly to the changing conditions of the battlefield, the military needs to compress the time that this process requires. Despite efforts to develop computer-based tools to automatically plan missions, combat planners still manually perform most of the tasking and scheduling of aircraft and targets. Unfortunately some of the tools currently available are perceived to be complicated and time consuming to use by the planners. They also …

Visualizing Early-Stage Breast Cancer Tumors In A Mammographic Environment Through A 3-Dimensional Mathematical Model, Christopher B. Bassham

Theses and Dissertations

In response to the insidious and deadly nature of breast cancer and the less-than-perfect detection ability of mammography, we develop a mathematical model as a foundation to the long-term goal of improving early breast cancer detection. By using modeling and simulation to construct an accurate breast cancer tumor model, we hope to solve the problems associated with mammogram misdiagnosis and, perhaps as a by-product, lend insight to tumor development dynamics. The final tumor model, written in MATLAB, provides realistic tumor growth and 2-dimensional visualization of 3-dimensional structures. Earlier modeling attempts capture slices of the tumor in the 2-dimensional growth spaces. …

Parallel Implementation Of An Artificial Neural Network Integrated Feature And Architecture Selection Algorithm, Craig W. Rizzo

Theses and Dissertations

The selection of salient features and an appropriate hidden layer architecture contributes significantly to the performance of a neural network. A number of metrics and methodologies exist for estimating these parameters. This research builds on recent efforts to integrate feature and architecture selection for the multilayer perceptron. In the first stage of work a current algorithm is developed in a parallel environment, significantly improving its efficiency and utility. In the second stage, improvements to the algorithm are proposed. With regards to feature selection, a common random number (CRN) addition is proposed. Two new methods of architecture selection are examined, to …

Embedding A Reactive Tabu Search Heuristic In Unmanned Aerial Vehicle Simulations, Joel L. Ryan

Theses and Dissertations

We apply a Reactive Tabu Search (RTS) heuristic within a discrete event simulation to solve routing problems for Unmanned Aerial Vehicles (UAVs). Our formulation represents this problem as a multiple Traveling Salesman Problem with time windows (mTSPTW), with the objective of attaining a specified level of target coverage using a minimum number of vehicles. Incorporating weather and probability of UAV survival at each target as random inputs, the RTS heuristic in the simulation searches for the best solution in each realization of the problem scenario in order to identify those routes that are robust to variations in weather, threat, or …

The Application Of Sequential Convex Programming To Large-Scale Structural Optimization Problems, Todd A. Sriver

Theses and Dissertations

Structural design problems are often modeled using finite element methods. Such models are often characterized by constraint functions that are not explicitly defined in terms of the design variables. These functions are typically evaluated through numerical finite element analysis (FEA). Optimizing large-scale structural design models requires computationally expensive FEAs to obtain function and gradient values. An optimization approach which uses the SCP sequential convex programming algorithm of Zillober, integrated as the optimizer in the Automated Structural Optimization System (ASTROS), is tested. The traditional approach forms an explicitly defined approximate subproblem at each design iteration that is solved using the method …

Clustering Algorithm For Local Area Network Design In A Cim Environment, A. C. Manjunath

Theses

Communication systems have come to be regarded as being one of the most important aspects in manufacturing enterprises in recent years. It continues to offer enormous potential for improving the efficiency of manufacturing enterprises through Computer Integrated Manufacturing (CIM). It is true however that this potential cannot be realized by developments on the communications front alone. Strategic and economic considerations in installing a communications system in a manufacturing environment is of vital significance.

This thesis, at the outset attempts to bring out some of the issues in the area of communications (research), specifically in relation to CIM. A perception of …