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Full-Text Articles in Engineering
Design Of The Layout Of A Manufacturing Facility With A Closed Loop Conveyor With Shortcuts Using Queueing Theory And Genetic Algorithms, Vernet Michael Lasrado
Design Of The Layout Of A Manufacturing Facility With A Closed Loop Conveyor With Shortcuts Using Queueing Theory And Genetic Algorithms, Vernet Michael Lasrado
Electronic Theses and Dissertations
With the ongoing technology battles and price wars in today's competitive economy, every company is looking for an advantage over its peers. A particular choice of facility layout can have a significant impact on the ability of a company to maintain lower operational expenses under uncertain economic conditions. It is known that systems with less congestion have lower operational costs. Traditionally, manufacturing facility layout problem methods aim at minimizing the total distance traveled, the material handling cost, or the time in the system (based on distance traveled at a specific speed). The proposed methodology solves the looped layout design problem …
Electimize A New Evolutionary Algorithm For Optimization With Applications In Construction Engineering, Raheem, Mohamed Abdel
Electimize A New Evolutionary Algorithm For Optimization With Applications In Construction Engineering, Raheem, Mohamed Abdel
Electronic Theses and Dissertations
Optimization is considered an essential step in reinforcing the efficiency of performance and economic feasibility of construction projects. In the past few decades, evolutionary algorithms (EAs) have been widely utilized to solve various types of construction-related optimization problems due to their efficiency in finding good solutions in relatively short time periods. However, in many cases, these existing evolutionary algorithms failed to identify the optimal solution to several optimization problems. As such, it is deemed necessary to develop new approaches in order to help identify better-quality solutions. This doctoral research presents the development of a new evolutionary algorithm, named “Electimize,” that …
An Adaptive Modular Redundancy Technique To Self-Regulate Availability, Area, And Energy Consumption In Mission-Critical Applications, Rawad N. Al-Haddad
An Adaptive Modular Redundancy Technique To Self-Regulate Availability, Area, And Energy Consumption In Mission-Critical Applications, Rawad N. Al-Haddad
Electronic Theses and Dissertations
As reconfigurable devices' capacities and the complexity of applications that use them increase, the need for self-reliance of deployed systems becomes increasingly prominent. A Sustainable Modular Adaptive Redundancy Technique (SMART) composed of a dual-layered organic system is proposed, analyzed, implemented, and experimentally evaluated. SMART relies upon a variety of self-regulating properties to control availability, energy consumption, and area used, in dynamically-changing environments that require high degree of adaptation. The hardware layer is implemented on a Xilinx Virtex-4 Field Programmable Gate Array (FPGA) to provide self-repair using a novel approach called a Reconfigurable Adaptive Redundancy System (RARS). The software layer supervises …
A Sustainable Autonomic Architecture For Organically Reconfigurable Computing Systems, Rashad S. Oreifej
A Sustainable Autonomic Architecture For Organically Reconfigurable Computing Systems, Rashad S. Oreifej
Electronic Theses and Dissertations
A Sustainable Autonomic Architecture for Organically Reconfigurable Computing System based on SRAM Field Programmable Gate Arrays (FPGAs) is proposed, modeled analytically, simulated, prototyped, and measured. Low-level organic elements are analyzed and designed to achieve novel self-monitoring, self-diagnosis, and self-repair organic properties. The prototype of a 2-D spatial gradient Sobel video edge-detection organic system use-case developed on a XC4VSX35 Xilinx Virtex-4 Video Starter Kit is presented. Experimental results demonstrate the applicability of the proposed architecture and provide the infrastructure to quantify the performance and overcome fault-handling limitations. Dynamic online autonomous functionality restoration after a malfunction or functionality shift due to changing …
Learning From Geometry In Learning For Tactical And Strategic Decision Domains, Jason Gauci
Learning From Geometry In Learning For Tactical And Strategic Decision Domains, Jason Gauci
Electronic Theses and Dissertations
Artificial neural networks (ANNs) are an abstraction of the low-level architecture of biological brains that are often applied in general problem solving and function approximation. Neuroevolution (NE), i.e. the evolution of ANNs, has proven effective at solving problems in a variety of domains. Information from the domain is input to the ANN, which outputs its desired actions. This dissertation presents a new NE algorithm called Hypercube-based NeuroEvolution of Augmenting Topologies (HyperNEAT), based on a novel indirect encoding of ANNs. The key insight in HyperNEAT is to make the algorithm aware of the geometry in which the ANNs are embedded and …
Alayzing The Effects Of Modularity On Search Spaces, Ozlem Garibay
Alayzing The Effects Of Modularity On Search Spaces, Ozlem Garibay
Electronic Theses and Dissertations
We are continuously challenged by ever increasing problem complexity and the need to develop algorithms that can solve complex problems and solve them within a reasonable amount of time. Modularity is thought to reduce problem complexity by decomposing large problems into smaller and less complex subproblems. In practice, introducing modularity into evolutionary algorithm representations appears to improve search performance; however, how and why modularity improves performance is not well understood. In this thesis, we seek to better understand the effects of modularity on search. In particular, what are the effects of module creation on the search space structure and how …
A Methodology For Minimizing The Oscillations In Supply Chains Using System Dynamics And Genetic Algorithms, Ramamoorthy C.V.V. Lakkoju
A Methodology For Minimizing The Oscillations In Supply Chains Using System Dynamics And Genetic Algorithms, Ramamoorthy C.V.V. Lakkoju
Electronic Theses and Dissertations
Supply Chain Management (SCM) is a critically significant strategy that enterprises depend on to meet challenges that they face because of highly competitive and dynamic business environments of today. Supply chain management involves the entire network of processes from procurement of raw materials/services/technologies to manufacturing or servicing intermediate products/services to converting them into final products or services and then distributing and retailing them till they reach final customers. A supply chain network by nature is a large and complex, engineering and management system. Oscillations occurring in a supply chain because of internal and/or external influences and measures to be taken …
Evolutionary Optimization Of Support Vector Machines, Fred Gruber
Evolutionary Optimization Of Support Vector Machines, Fred Gruber
Electronic Theses and Dissertations
Support vector machines are a relatively new approach for creating classifiers that have become increasingly popular in the machine learning community. They present several advantages over other methods like neural networks in areas like training speed, convergence, complexity control of the classifier, as well as a stronger mathematical background based on optimization and statistical learning theory. This thesis deals with the problem of model selection with support vector machines, that is, the problem of finding the optimal parameters that will improve the performance of the algorithm. It is shown that genetic algorithms provide an effective way to find the optimal …
The Proteomics Approach To Evolutionary Computation: An Analysis Of Pr, Ivan Garibay
The Proteomics Approach To Evolutionary Computation: An Analysis Of Pr, Ivan Garibay
Electronic Theses and Dissertations
As the complexity of our society and computational resources increases, so does the complexity of the problems that we approach using evolutionary search techniques. There are recent approaches to deal with the problem of scaling evolutionary methods to cope with highly complex difficult problems. Many of these approaches are biologically inspired and share an underlying principle: a problem representation based on basic representational building blocks that interact and self-organize into complex functions or designs. The observation from the central dogma of molecular biology that proteins are the basic building blocks of life and the recent advances in proteomics on analysis …