926 resultados para systems optimization
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The purpose of this article is to show the applicability and benefits of the techniques of design of experiments as an optimization tool for discrete simulation models. The simulated systems are computational representations of real-life systems; its characteristics include a constant evolution that follows the occurrence of discrete events along the time. In this study, a production system, designed with the business philosophy JIT (Just in Time) is used, which seeks to achieve excellence in organizations through waste reduction in all the operational aspects. The most typical tool of JIT systems is the KANBAN production control that seeks to synchronize demand with flow of materials, minimize work in process, and define production metrics. Using experimental design techniques for stochastic optimization, the impact of the operational factors on the efficiency of the KANBAN / CONWIP simulation model is analyzed. The results show the effectiveness of the integration of experimental design techniques and discrete simulation models in the calculation of the operational parameters. Furthermore, the reliability of the methodologies found was improved with a new statistical consideration.
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In a northern European climate a typical solar combisystem for a single family house normally saves between 10 and 30 % of the auxiliary energy needed for space heating and domestic water heating. It is considered uneconomical to dimension systems for higher energy savings. Overheating problems may also occur. One way of avoiding these problems is to use a collector that is designed so that it has a low optical efficiency in summer, when the solar elevation is high and the load is small, and a high optical efficiency in early spring and late fall when the solar elevation is low and the load is large.The study investigates the possibilities to design the system and, in particular, the collector optics, in order to match the system performance with the yearly variations of the heating load and the solar irradiation. It seems possible to design practically viable load adapted collectors, and to use them for whole roofs ( 40 m2) without causing more overheating stress on the system than with a standard 10 m2 system. The load adapted collectors collect roughly as much energy per unit area as flat plate collectors, but they may be produced at a lower cost due to lower material costs. There is an additional potential for a cost reduction since it is possible to design the load adapted collector for low stagnation temperatures making it possible to use less expensive materials. One and the same collector design is suitable for a wide range of system sizes and roof inclinations. The report contains descriptions of optimized collector designs, properties of realistic collectors, and results of calculations of system output, stagnation performance and cost performance. Appropriate computer tools for optical analysis, optimization of collectors in systems and a very fast simulation model have been developed.
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This paper presents an efficient approach based on recurrent neural network for solving nonlinear optimization. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid subspace technique. These parameters guarantee the convergence of the network to the equilibrium points that represent an optimal feasible solution. The main advantage of the developed network is that it treats optimization and constraint terms in different stages with no interference with each other. Moreover, the proposed approach does not require specification of penalty and weighting parameters for its initialization. A study of the modified Hopfield model is also developed to analyze its stability and convergence. Simulation results are provided to demonstrate the performance of the proposed neural network. (c) 2005 Elsevier B.V. All rights reserved.
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A neural model for solving nonlinear optimization problems is presented in this paper. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid-subspace technique. These parameters guarantee the convergence of the network to the equilibrium points that represent an optimal feasible solution. The network is shown to be completely stable and globally convergent to the solutions of nonlinear optimization problems. A study of the modified Hopfield model is also developed to analyze its stability and convergence. Simulation results are presented to validate the developed methodology.
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National Highway Traffic Safety Administration, Washington, D.C.
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This paper aims to analyze dual-purpose systems focusing the total cost optimization; a superstructure is proposed to present cogeneration systems and desalination technologies alternatives for the synthesis process. The superstructure consists of excluding components, gas turbines or conventional steam generators with excluding alternatives of supplying fuel for each combustion system. Also, backpressure or condensing/extraction steam turbine for supplying process steam could be selected. Finally one desalination unit chosen between electrically-driven or steam-driven reverse osmosis. multi-effect and multistage flash should be included. The analysis herein performed is based on energy and mass conservation equations, as well as the technological limiting equation of equipment. The results for ten different commercial gas turbines revealed that electrically-driven reverse osmosis was always chosen together with both natural gas and gasified biomass gas turbines. (C) 2009 Elsevier B.V. All rights reserved.
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Abstract : Wastepaper sludge ash (WSA) is generated by a cogeneration station by burning wastepaper sludge. It mainly consists of amorphous aluminosilicate phase, anhydrite, gehlenite, calcite, lime, C2S, C3A, quartz, anorthite, traces of mayenite. Because of its free lime content (~10%), WSA suspension has a high pH (13). Previous researchers have found that the WSA composition has poor robustness and the variations lead to some unsoundness for Portland cement (PC) blended WSA concrete. This thesis focused on the use of WSA in different types of concrete mixes to avoid the deleterious effect of the expansion due to the WSA hydration. As a result, WSA were used in making alkali-activated materials (AAMs) as a precursor source and as a potential activator in consideration of its amorphous content and the high alkaline nature. Moreover, the autogenous shrinkage behavior of PC concrete at low w/b ratio was used in order to compensate the expansion effect due to WSA. The concrete properties as well as the volume change were investigated for the modified WSA blended concrete. The reaction mechanism and microstructure of newly formed binder were evaluated by X-ray diffraction (XRD), calorimetry, thermogravimetric analysis (TGA), scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDX). When WSA was used as precursor, the results showed incompatible reaction between WSA and alkaline solution. The mixtures were not workable and provided very low compressive strength no matter what kinds of chemical activators were used. This was due to the metallic aluminum in WSA, which releases abundant hydrogen gas when WSA reacts with strong alkaline solution. Besides, the results of this thesis showed that WSA can activate the glassy phase contained in slag, glass powder (GP) and class F fly ash (FFA) with an optimum blended ratio of 50:50. The WSA/slag (mass ratio of 50:50) mortar (w/b of 0.47) attained 46 MPa at 28 days without heat curing assistance. A significant fast setting was noticed for the WSA-activated binder due to the C3A phase, free lime and metallic aluminum contained in the WSA. Adding 5% of gypsum can delay the fast setting, but this greatly increased the potential risk of intern sulfate attack. The XRD, TGA and calorimetry analyses demonstrated the formation of ettringite, C-S-H, portlandite, hydrogarnet and calcium carboaluminate in the hydrated binder. The mechanical performance of different binder was closely related to the microstructure of corresponding binder which was proved by the SEM observation. The hydrated WSA/slag and WSA/FFA binder formed a C-A-S-H type of gel with lower Ca/Si ratio (0.47~1.6). A hybrid gel (i.e. C-N-A-S-H) was observed for the WSA/GP binder with a very low Ca/Si ratio (0.26) and Na/Si ratio (0.03). The SEM/EDX analyses displayed the formation of expansive gel (ettringite and thaumasite) in the gypsum added WSA/slag concrete. The gradual emission of hydrogen gas due to the reaction of WSA with alkaline environment significantly increased the porosity and degraded the microstructure of hydrated matrix after the setting. In the last phase of this research WSA-PC blended binder was tailored to form a high autogenous shrinkage concrete in order to compensate the initial expansion. Different binders were proportioned with PC, WSA, silica fume or slag. The microstructure and mechanical properties of concrete can be improved by decreasing w/b ratios and by incorporating silica fume or slag. The 28-day compressive strength of WSA-blended concrete was above 22 MPa and reached 45 MPa when silica fume was added. The PC concrete incorporating silica fume or slag tended to develop higher autogenous shrinkage at low w/b ratios, and thus the ternary binder with the addition of WSA inhibited the long term shrinkage due to the initial expansion property to WSA. In the restrained shrinkage test, the concrete ring incorporating the ternary binder (PC/WSA/slag) revealed negligible potential to cracking up to 96 days as a result of the offset effect by WSA expansion. The WSA blended regular concrete could be produced for potential applications with reduced expansion, good mechanical property and lower permeability.
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Most of water distribution systems (WDS) need rehabilitation due to aging infrastructure leading to decreasing capacity, increasing leakage and consequently low performance of the WDS. However an appropriate strategy including location and time of pipeline rehabilitation in a WDS with respect to a limited budget is the main challenge which has been addressed frequently by researchers and practitioners. On the other hand, selection of appropriate rehabilitation technique and material types is another main issue which has yet to address properly. The latter can affect the environmental impacts of a rehabilitation strategy meeting the challenges of global warming mitigation and consequent climate change. This paper presents a multi-objective optimization model for rehabilitation strategy in WDS addressing the abovementioned criteria mainly focused on greenhouse gas (GHG) emissions either directly from fossil fuel and electricity or indirectly from embodied energy of materials. Thus, the objective functions are to minimise: (1) the total cost of rehabilitation including capital and operational costs; (2) the leakage amount; (3) GHG emissions. The Pareto optimal front containing optimal solutions is determined using Non-dominated Sorting Genetic Algorithm NSGA-II. Decision variables in this optimisation problem are classified into a number of groups as: (1) percentage proportion of each rehabilitation technique each year; (2) material types of new pipeline for rehabilitation each year. Rehabilitation techniques used here includes replacement, rehabilitation and lining, cleaning, pipe duplication. The developed model is demonstrated through its application to a Mahalat WDS located in central part of Iran. The rehabilitation strategy is analysed for a 40 year planning horizon. A number of conventional techniques for selecting pipes for rehabilitation are analysed in this study. The results show that the optimal rehabilitation strategy considering GHG emissions is able to successfully save the total expenses, efficiently decrease the leakage amount from the WDS whilst meeting environmental criteria.
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We consider an infinite horizon optimal impulsive control problems for which a given cost function is minimized by choosing control strategies driving the state to a point in a given closed set C ∞. We present necessary conditions of optimality in the form of a maximum principle for which the boundary condition of the adjoint variable is such that non-degeneracy due to the fact that the time horizon is infinite is ensured. These conditions are given for conventional systems in a first instance and then for impulsive control problems. They are proved by considering a family of approximating auxiliary interval conventional (without impulses) optimal control problems defined on an increasing sequence of finite time intervals. As far as we know, results of this kind have not been derived previously. © 2010 IFAC.
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The development of new technologies that use peer-to-peer networks grows every day, with the object to supply the need of sharing information, resources and services of databases around the world. Among them are the peer-to-peer databases that take advantage of peer-to-peer networks to manage distributed knowledge bases, allowing the sharing of information semantically related but syntactically heterogeneous. However, it is a challenge to ensure the efficient search for information without compromising the autonomy of each node and network flexibility, given the structural characteristics of these networks. On the other hand, some studies propose the use of ontology semantics by assigning standardized categorization of information. The main original contribution of this work is the approach of this problem with a proposal for optimization of queries supported by the Ant Colony algorithm and classification though ontologies. The results show that this strategy enables the semantic support to the searches in peer-to-peer databases, aiming to expand the results without compromising network performance. © 2011 IEEE.
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The relationship between the optimization of the potential function and the foldability of theoretical protein models is studied based on investigations of a 27-mer cubic-lattice protein model and a more realistic lattice model for the protein crambin. In both the simple and the more complicated systems, optimization of the energy parameters achieves significant improvements in the statistical-mechanical characteristics of the systems and leads to foldable protein models in simulation experiments. The foldability of the protein models is characterized by their statistical-mechanical properties--e.g., by the density of states and by Monte Carlo folding simulations of the models. With optimized energy parameters, a high level of consistency exists among different interactions in the native structures of the protein models, as revealed by a correlation function between the optimized energy parameters and the native structure of the model proteins. The results of this work are relevant to the design of a general potential function for folding proteins by theoretical simulations.
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Declarative techniques such as Constraint Programming can be very effective in modeling and assisting management decisions. We present a method for managing university classrooms which extends the previous design of a Constraint-Informed Information System to generate the timetables while dealing with spatial resource optimization issues. We seek to maximize space utilization along two dimensions: classroom use and occupancy rates. While we want to maximize the room use rate, we still need to satisfy the soft constraints which model students’ and lecturers’ preferences. We present a constraint logic programming-based local search method which relies on an evaluation function that combines room utilization and timetable soft preferences. Based on this, we developed a tool which we applied to the improvement of classroom allocation in a University. Comparing the results to the current timetables obtained without optimizing space utilization, the initial versions of our tool manages to reach a 30% improvement in space utilization, while preserving the quality of the timetable, both for students and lecturers.
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射频识别技术(Radio Frequency Identification, RFID)作为采集与处理信息的高新技术和信息化标准的基础,被列为本世纪十大重要技术之一。但是,RFID技术的大规模实际应用仍处于探索阶段,RFID系统的应用基础技术还存在着大量尚未解决的关键问题,其中RFID系统优化是RFID技术研究和应用的重要课题。由于RFID系统本身的动态性和不确定性, RFID系统优化面对的一般是非线性、多目标、大规模的复杂优化问题,传统的数学优化算法在处理这些问题时,存在困难。为此,研究新的优化算法成为RFID技术实际应用和理论研究中必须解决的课题。 智能计算方法是求解复杂RFID系统优化问题的一种可供选择的算法。智能计算作为一个新兴领域,其发展已引起了多个学科领域研究人员的关注,目前已经成为人工智能、经济、社会、生物等交叉学科的研究热点和前沿领域。智能计算的各类算法已在传统NP问题求解及诸多实际应用领域中展现出其优异的性能和巨大的发展潜力。 本文旨在对RFID系统的各种优化问题进行深入研究和探讨,面向RFID技术的实际应用需求构建其优化模型,并基于智能计算思想设计能够有效求解这些复杂模型的新型智能优化算法。具体研究内容包括: 首先,进行了RFID读写器网络的调度问题研究。在深入分析RFID网络中读写器冲突类型和成因的基础上,考虑RFID网络中的读写器冲突约束,以最小化系统中的频道数量、时隙分配以及总处理时间建立了RFID读写器网络调度的数学优化模型。从生物学的角度出发提出基于生态捕食模型的改进PSO算法(Particle Swarm Optimizer based on Predator-prey Coevolution, PSOPC),在一定程度上解决了PSO算法在迭代后期随着多样性丧失而陷入局部最优的缺点。应用PSOPC设计了求解RFID读写器网络调度模型的智能求解算法,分别给出算法的求解框架、关键步骤的实现机制。通过在不同规模的RFID读写器网络上进行实例仿真,验证了算法的有效性和模型的正确性。 其次,进行了基于菌群自适应觅食算法RFID网络规划问题的研究。考虑RFID系统在不同应用环境下的系统需求,建立了RFID网络规化的数学模型,其目标函数分别为:RFID网络标签覆盖率的最大化目标函数、RFID读写器冲突的最小化目标函数、RFID网络运行的经济效益最大化目标函数、RFID网络运行的负载平衡目标函数以及同时考虑全局目标的混合目标函数。将自然界生物觅食所采用的自适应搜索策略与细菌的趋化行为和群体感应机制相集成,提出了适合求解复杂RFID网络规划问题的菌群自适应觅食算法(Adaptive Bacterial Foraging Optimization, ABFO)。通过仿真实验基于ABFO算法分别对RFID网络规划模型中的五个目标函数进行了实例求解和分析,测试结果与标准PSO算法和遗传算法进行了比较分析。 再次,进行了基于系统智能方法的RFID网络规划分布式决策模型研究。采用分布式决策的思想建立了RFID网络规划的层次模型,在一定程度上缓解、分散了RFID网络规划问题的复杂性,以解决具有混合变量(包括离散变量和连续变量)的多目标RFID网络规划问题。针对层次模型求解的复杂性,以复杂适应系统理论为指导思想设计了一种新型系统智能优化算法对RFID网络规划的层次模型进行求解。系统智能算法将群体智能中的单层群体系统概念扩展为多层涌现系统,仿真实验表明新提出的算法显著提高了智能计算方法的寻优能力,以及算法的适应性、鲁棒性和平衡性等性能。 最后,进行了RFID网络目标跟踪系统中的数据融合研究。以基于RFID技术的目标定位与跟踪系统为应用背景,提出了基于模糊聚类方法的多RFID读写器数据融合模型框架。通过深入分析蜜蜂采蜜的基本生物学规律,对蜜蜂的个体行为及群体行为进行模拟,提出了一类新型群体智能优化算法-蜂群优化算法(Bee Swarm Optimization, BSO),并将BSO算法嵌入RFID目标定位跟踪系统,作为其模糊聚类的基本算法。仿真研究表明,提出的融合模型能够有效的过滤读写器对跟踪目标的错误监测数据,显著提高目标定位与跟踪的精度。
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Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Automação e Electrónica Industrial