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IEEE Congress on Evolutionary Computation

作者： Dos Santos Coelho, Leandro De Andrade Bernert, Diego Luis Mariani, Viviana Cocco Industrial and Systems Engineering Graduate Program PPGEPS Pontifical Catholic University of Paran Imaculada Conceição 1155 80215-901 Curitiba Paraná Brazil Department of Mechanical Engineering PPGEM Pontifical Catholic University of Paran Imaculada Conceição 1155 80215-901 Curitiba Paran Brazil

ISBN: (纸本)9781424478347

The reliability-redundancy allocation problem can be approached as a mixed-integer programming problem. It has been solved by using optimization techniques such as dynamic programming, integer programming, and mixed-integer nonlinear programming. On the other hand, a broad class of meta-heuristics has been developed for reliability-redundancy optimization. Recently, a new meta-heuristics called firefly algorithm (FA) algorithm has emerged. The FA is a stochastic metaheuristic approach based on the idealized behavior of the flashing characteristics of fireflies. In FA, the flashing light can be formulated in such a way that it is associated with the objective function to be optimized, which makes it possible to formulate the firefly algorithm. This paper introduces a modified FA approach combined with chaotic sequences (FAC) applied to reliability-redundancy optimization. In this context, an example of mixed integer programming in reliability-redundancy design of an overspeed protection system for a gas turbine is evaluated. In this application domain, FAC was found to outperform the previously best-known solutions available. © 2011 IEEE.

关键词： Integer programming

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Hardware Particle Swarm Optimization with passive congregation for embedded applications

Hardware Particle Swarm Optimization with passive congregati...

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Southern Conference on programmable Logic

作者： Muñoz, Daniel M. Llanos, Carlos H. Coelho, Leandro Dos S. Ayala-Rincón, Mauricio Department of Mechanical Engineering Automation and Control Group/GRACO University of Brasilia Brasilia D.F. Brazil Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana Curitiba Parana Brazil Department of Computer Science and Mathematics University of Brasilia Brasilia D.F. Brazil

ISBN: (纸本)9781424488483

Achieving high performance optimization algorithms for embedded applications can be very challenging, particularly when several requirements such as high accuracy computations, short elapsed time, area cost, low power consumption and portability must be accomplished. This paper proposes a hardware implementation of the Particle Swarm Optimization algorithm with passive congregation (HPPSOpc), which was developed using several floating-point arithmetic libraries. The passive congregation is a biological behavior which allows the swarm to preserve its integrity, balancing between global and local search. The HPPSOpc architecture was implemented on a Virtex5 FPGA device and validated using two multimodal benchmark problems. Synthesis, simulation and execution time results demonstrates that the passive congregation approach is a low cost solution for solving embedded optimization problems with a high performance. © 2011 IEEE.

关键词： Digital arithmetic

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Opposition-based shuffled PSO with passive congregation applied to FM matching synthesis

Opposition-based shuffled PSO with passive congregation appl...

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IEEE Congress on Evolutionary Computation

作者： Munoz, Daniel M. Llanos, Carlos H. Dos S. Coelho, Leandro Ayala-Rincon, Mauricio Department of Mechanical Engineering Automation and Control Group/GRACO University of Brasilia Brasilia D.F. Brazil Industrial and Systems Engineering Graduate Program LAS/PPGEPS Pontifical Catholic University of Parana Curitiba Parana Brazil Department of Computer Science and Mathematics University of Brasilia Brasilia D.F. Brazil

ISBN: (纸本)9781424478347

Synthesis of musical instruments or human voice is a time consuming process which requires theoretical and experimental knowledge about the synthesis engine. Commonly, performers need to deal with synthesizer interfaces and a process of trial and error for creating musical sounds similar to a target sound. This drawback can be overcome by adjusting automatically the synthesizer parameters using optimization algorithms. In this paper a hybrid particle swarm optimization (PSO) algorithm is proposed to solve the frequency modulation (FM) matching synthesis problem. The proposed algorithm takes advantage of a shuffle process for exchanging information between particles and applies the selective passive congregation and the opposition-based learning approaches to preserve swarm diversity. Both approaches for injecting diversity are based on simple operators, preserving the easy implementation philosophy of the particle swarm optimization. The proposed hybrid particle swarm optimization algorithm was validated for a three-nested FM synthesizer, which represents a 6-dimensional multimodal optimization problem with strong epistasis. Simulation results revealed that the proposed algorithm presented promising results in terms of quality of solutions. © 2011 IEEE.

关键词： Global optimization

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Improved quantum-inspired evolutionary algorithm with diversity information applied to economic dispatch problem with prohibited operating zones

Improved quantum-inspired evolutionary algorithm with divers...

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作者： Neto, Júlio Xavier Vianna De Andrade Bernert, Diego Luis Dos Santos Coelho, Leandro Pontifical Catholic University of Parana PUCPR Undergraduate Program at Mechatronics Engineering Imaculada Conceição 1155 Zip code 80215-901 Curitiba Parana Brazil Pontifical Catholic University of Parana PUCPR Industrial and Systems Engineering Graduate Program LAS/PPGEPS Imaculada Conceição 1155 80215-901 Curitiba Parana Brazil

The objective of the economic dispatch problem (EDP) of electric power generation, whose characteristics are complex and highly nonlinear, is to schedule the committed generating unit outputs so as to meet the required load demand at minimum operating cost while satisfying all unit and system equality and inequality constraints. Recently, as an alternative to the conventional mathematical approaches, modern meta-heuristic optimization techniques have been given much attention by many researchers due to their ability to find an almost global optimal solution in EDPs. Research on merging evolutionary computation and quantum computation has been started since late 1990. Inspired on the quantum computation, this paper presented an improved quantum-inspired evolutionary algorithm (IQEA) based on diversity information of population. A classical quantum-inspired evolutionary algorithm (QEA) and the IQEA were implemented and validated for a benchmark of EDP with 15 thermal generators with prohibited operating zones. From the results for the benchmark problem, it is observed that the proposed IQEA approach provides promising results when compared to various methods available in the literature. © 2010 Elsevier Ltd. All rights reserved.

关键词： Optimization

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Machining processes for sapphire wafers: A literature review

Machining processes for sapphire wafers: A literature review

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作者： Li, Z.C. Pei, Z.J. Funkenbusch, P.D. Department of Industrial and Systems Engineering North Carolina Agricultural and Technical State University Greensboro NC 27411 United States Department of Industrial and Manufacturing Systems Engineering Kansas State University Manhattan KS United States Materials Science Program Department of Mechanical Engineering Hajim School of Engineering and Applied Sciences Rochester NY United States

Sapphire wafers are widely used as the substrates for fabricating GaN light-emitting diodes (LEDs). The quality of LEDs depends directly on the quality of the sapphire wafers. A series of machining processes is required to turn sapphire barstock into wafers with the desired geometry and surface quality. This paper reviews the literature on various machining processes for sapphire wafers: slicing (including outer diameter cut-off grinding, inner diameter cut-off grinding, loose abrasive multi-wire sawing, fixed abrasive slicing, and fixed abrasive multi-wire sawing), flattening (including lapping and grinding), and surface finishing (including mechanical polishing and chemical mechanical polishing). New machining technologies are also introduced.

关键词： Grinding (machining)

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Compensability of errors in product quality in multistage manufacturing processes

Compensability of errors in product quality in multistage ma...

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作者： Jiao, Yibo Djurdjanovic, Dragan Department of Mechanical Engineering Graduate Program in Operations Research and Industrial Engineering University of Texas at Austin 1 University Station C2200 Austin TX 78712-0292 United States Department of Mechanical Engineering Advanced Manufacturing Research Center University of Texas at Austin 1 University Station C2200 Austin TX 78712-0292 United States

Recent advances in model-based feedforward control of quality in multistage manufacturing processes (MMPs) are used to introduce the concept of compensability of errors in product quality. It is defined as the system-level ability to automatically eliminate quality errors accumulated in the product, given the allocation of measurements and controllable tooling. Significant similarities are observed with the control theory concepts of controllability and observability. In addition, just like in control theory, it is shown that relatively simple matrix rank tests can be used to determine the compensability of a MMP and are related with the previously introduced notion of diagnosability. The theory introduced in this paper enables rapid quantitative analysis of one's ability to actively control the quality in a manufacturing system, which is crucial for optimal allocation of measurements and controllable tooling in an MMP. Compensability studies based on the newly introduced methods are conducted using models of the flow of errors in product quality in two automotive cylinder head machining lines and a multi-layer semiconductor lithography process.

关键词： Errors

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A chaotic firefly algorithm applied to reliability-redundancy optimization

A chaotic firefly algorithm applied to reliability-redundanc...

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Congress on Evolutionary Computation

作者： Leandro dos Santos Coelho Diego Luís de Andrade Bernert Viviana Cocco Mariani Industrial and Systems Engineering Graduate Program PPGEPS Pontifical Catholic University of Paraná Curitiba Parana Brazil Department of Mechanical Engineering PPGEPS Pontifical Catholic University of Paraná Curitiba Parana Brazil

The reliability-redundancy allocation problem can be approached as a mixed-integer programming problem. It has been solved by using optimization techniques such as dynamic programming, integer programming, and mixed-integer non linear programming. On the other hand, a broad class of meta heuristics has been developed for reliability-redundancy optimization. Recently, a new meta-heuristics called firefly algorithm (FA) algorithm has emerged. The FA is a stochastic metaheuristic approach based on the idealized behavior of the flashing characteristics of fireflies. In FA, the flashing light can be formulated in such a way that it is associated with the objective function to be optimized, which makes it possible to formulate the firefly algorithm. This paper introduces a modified FA approach combined with chaotic sequences (FAC) applied to reliability-redundancy optimization. In this context, an example of mixed integer programming in reliability-redundancy design of an overspeed protection system for a gas turbine is evaluated. In this application domain, FAC was found to outperform the previously best-known solutions available.

关键词： Fires Optimization Chaos Algorithm design and analysis Benchmark testing Redundancy

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A normative differential evolution approach for estimation of heat transfer coefficient during freezing treatment by inverse analysis

A normative differential evolution approach for estimation o...

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Congress on Evolutionary Computation

作者： Viviana Cocco Mariani Carlos Eduardo Klein Luiz Guilherme Justi Luvizotto Leandro dos Santos Coelho Department of Mechanical Engineering PPGEM Pontifical Catholic University of Paraná Curitiba Parana Brazil Industrial and Systems Engineering Graduate Program PPGEPS Pontifical Catholic University of Paraná Curitiba Parana Brazil

Among the existing meta-heuristic optimization algorithms, a well-known branch is the differential evolution (DE). DE is a powerful population-based algorithm of evolutionary computation field designed for solving global optimization problems which only has a few control parameters. With an eye to improve the performance of DE, in this paper, a DE approach combined with a cultural algorithm technique based on normative knowledge (NDE) is investigated to estimate the heat transfer coefficient during freezing treatment by inverse analysis. Numerical results for inverse heat transfer problem demonstrate the applicability and efficiency of the NDE algorithm. In this application, NDE approach outperforms a classical DE approach in terms of quality of solution.

关键词： Heat transfer Optimization Temperature measurement Cultural differences Algorithm design and analysis Evolutionary computation Temperature

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A Radial Basis Function Spike Model for Indirect Learning via Integrate-and-Fire Sampling and Reconstruction Techniques

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Advances in Artificial Neural systems 2012年第1期2012卷

作者： X. Zhang G. Foderaro C. Henriquez A. M. J. VanDongen S. Ferrari Laboratory for Intelligent Systems and Control (LISC) Department of Mechanical Engineering and Materials Science Duke University Durham NC 27708 USAduke.edu Department of Biomedical Engineering and Department of Computer Science Duke University Durham NC 27708 USAduke.edu Program in Neuroscience & Behavioral Disorders Duke-NUS Graduate Medical School Singapore Singapore

This paper presents a deterministic and adaptive spike model derived from radial basis functions and a leaky integrate-and-fire sampler developed for training spiking neural networks without direct weight manipulation. Several algorithms have been proposed for training spiking neural networks through biologically-plausible learning mechanisms, such as spike-timing-dependent synaptic plasticity and Hebbian plasticity. These algorithms typically rely on the ability to update the synaptic strengths, or weights, directly, through a weight update rule in which the weight increment can be decided and implemented based on the training equations. However, in several potential applications of adaptive spiking neural networks, including neuroprosthetic devices and CMOS/memristor nanoscale neuromorphic chips, the weights cannot be manipulated directly and, instead, tend to change over time by virtue of the pre- and postsynaptic neural activity. This paper presents an indirect learning method that induces changes in the synaptic weights by modulating spike-timing-dependent plasticity by means of controlled input spike trains. In place of the weights, the algorithm manipulates the input spike trains used to stimulate the input neurons by determining a sequence of spike timings that minimize a desired objective function and, indirectly, induce the desired synaptic plasticity in the network.

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Adaptive fault-tolerant control based on hybrid redundancy

Adaptive fault-tolerant control based on hybrid redundancy

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作者： Takahashi, Masanori Takagi, Taro Department of Mechanical Systems Engineering Tokai University at Kumamoto 9-1-1 Toroku Kumamoto 862-8652 Japan Graduate School of Industrial Engineering Tokai University at Kumamoto 9-1-1 Toroku Kumamoto 862-8652 Japan

This paper presents a new adaptive fault-tolerant control system (AFTCS) against actuator failures. The AFTCS utilizes a hybrid of static and dynamic redundancies. In order to maintain the control performance, the redundancy-mode is selected appropriately to remove the effect of the failure. All the switching actions are executed based on only the input and error signals. Hence, any fault detector is not exploited. Furthermore, introducing an adaptive high-gain feedback controller makes it possible to achieve the λ-tracking in the presence of failure. In this paper, several simulation results for the CSTR are shown to confirm the effectiveness of the AFTCS. © 2011 Zhejiang University.

关键词： Redundancy

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