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Literatura académica sobre el tema "Response Optimization algorithms"

Autor: Grafiati

Publicado: 4 de junio de 2021

Última modificación: 2 de febrero de 2022

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Artículos de revistas sobre el tema "Response Optimization algorithms"

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Aungkulanon, Pasura. "A Comparative Study of Global-Best Harmony Search and Bat Algorithms on Optimization Problems." Applied Mechanics and Materials 464 (November 2013): 352–57. http://dx.doi.org/10.4028/www.scientific.net/amm.464.352.

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The engineering optimization problems are large and complex. Effective methods for solving these problems using a finite sequence of instructions can be categorized into optimization and meta-heuristics algorithms. Meta-heuristics techniques have been proved to solve various real world problems. In this study, a comparison of two meta-heuristic techniques, namely, Global-Best Harmony Search algorithm (GHSA) and Bat algorithm (BATA), for solving constrained optimization problems was carried out. GHSA and BATA are optimization algorithms inspired by the structure of harmony improvisation search

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Yeniay, Özgür. "Comparative Study of Algorithms for Response Surface Optimization." Mathematical and Computational Applications 19, no. 1 (2014): 93–104. http://dx.doi.org/10.3390/mca19010093.

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Shaaban, Amr Ahmed, and Omar Mahmoud Shehata. "Combining Response Surface Method and Metaheuristic Algorithms for Optimizing SPIF Process." International Journal of Manufacturing, Materials, and Mechanical Engineering 11, no. 4 (2021): 1–25. http://dx.doi.org/10.4018/ijmmme.2021100101.

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Recently, studies have focused on optimization as a method to reach the finest conditions for metal forming processes. This study tests various optimization techniques to determine the optimum conditions for single point incremental forming (SPIF). SPIF is a die-less forming process that depends on moving a tool along a path designed for a specific feature. As it involves various parameters, optimization based on experimental studies would be costly, hence a finite element model (FE-model) for the SPIF process is developed and validated through experimental results. In the second phase, statis

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Meng, Fanlin, Kui Weng, Balsam Shallal, Xiangping Chen, and Monjur Mourshed. "Forecasting Algorithms and Optimization Strategies for Building Energy Management & Demand Response." Proceedings 2, no. 15 (2018): 1133. http://dx.doi.org/10.3390/proceedings2151133.

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In this paper, we look at the key forecasting algorithms and optimization strategies for the building energy management and demand response management. By conducting a combined and critical review of forecast learning algorithms and optimization models/algorithms, current research gaps and future research directions and potential technical routes are identified. To be more specific, ensemble/hybrid machine learning algorithms and deep machine learning algorithms are promising in solving challenging energy forecasting problems while large-scale and distributed optimization algorithms are the fu

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Chapman, Archie C., Alex Rogers, Nicholas R. Jennings, and David S. Leslie. "A unifying framework for iterative approximate best-response algorithms for distributed constraint optimization problems." Knowledge Engineering Review 26, no. 4 (2011): 411–44. http://dx.doi.org/10.1017/s0269888911000178.

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AbstractDistributed constraint optimization problems (DCOPs) are important in many areas of computer science and optimization. In a DCOP, each variable is controlled by one of many autonomous agents, who together have the joint goal of maximizing a global objective function. A wide variety of techniques have been explored to solve such problems, and here we focus on one of the main families, namely iterative approximate best-response algorithms used as local search algorithms for DCOPs. We define these algorithms as those in which, at each iteration, agents communicate only the states of the v

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Saha, Suman Kumar, R. Kar, D. Mandal, and S. P. Ghoshal. "A Novel Firefly Algorithm for Optimal Linear Phase FIR Filter Design." International Journal of Swarm Intelligence Research 4, no. 2 (2013): 29–48. http://dx.doi.org/10.4018/jsir.2013040102.

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Optimal digital filter design in digital signal processing has thrown a growing influence on communication systems. FIR filter design involves multi-parameter optimization, on which the existing optimization algorithms do not work efficiently. For which different optimization techniques can be utilized to determine the impulse response coefficient of a filter and try to meet the ideal frequency response characteristics. In this paper, FIR low pass, high pass, band pass and band stop filters have been designed using a new meta-heuristic search method, called firefly algorithm. Firefly Algorithm

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Majumder, Arindam. "Optimization of Modern Manufacturing Processes Using Three Multi-Objective Evolutionary Algorithms." International Journal of Swarm Intelligence Research 12, no. 3 (2021): 96–124. http://dx.doi.org/10.4018/ijsir.2021070105.

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The optimization in manufacturing processes refers to the investigation of multiple responses simultaneously. Therefore, it becomes very necessary to introduce a technique that can solve the multiple response optimization problem efficiently. In this study, an attempt has been taken to find the application of three newly introduced multi-objective evolutionary algorithms, namely multi-objective dragonfly algorithm (MODA), multi-objective particle swarm optimization algorithm (MOPSO), and multi-objective teaching-learning-based optimization (MOTLBO), in the modern manufacturing processes. For t

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Sahu, Neelesh Kumar, and Atul B. Andhare. "Multiobjective optimization for improving machinability of Ti-6Al-4V using RSM and advanced algorithms." Journal of Computational Design and Engineering 6, no. 1 (2018): 1–12. http://dx.doi.org/10.1016/j.jcde.2018.04.004.

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Abstract This paper explores use of Teaching Learning Based Optimization (TLBO), ‘JAYA’ (Sanskrit word means Victory) and Genetic Algorithm (GA) for the combined minimization of roughness of machined surface and forces generated in cutting in turning of Ti-6Al-4V. Experimentation was carried out with Response Surface Methodology (RSM) and the Central Composite Design (CCD). Speed of cutting (m/min), feed rate (mm/min) and depth of cut (mm) were the design variables for optimization. Two responses (roughness of machined surface and force of cutting) were independently minimized. RSM was useful

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Tahmasebi, Mehrdad, Jagadeesh Pasupuleti, Fatemeh Mohamadian, et al. "Optimal Operation of Stand-Alone Microgrid Considering Emission Issues and Demand Response Program Using Whale Optimization Algorithm." Sustainability 13, no. 14 (2021): 7710. http://dx.doi.org/10.3390/su13147710.

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Microgrids are new technologies for integrating renewable energies into power systems. Optimal operation of renewable energy sources in standalone micro-grids is an intensive task due to the continuous variation of their output powers and intermittant nature. This work addresses the optimum operation of an independent microgrid considering the demand response program (DRP). An energy management model with two different scenarios has been proposed to minimize the costs of operation and emissions. Interruptible/curtailable loads are considered in DRPs. Besides, due to the growing concern of the

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Kapgate, Deepak. "Predictive Data Center Selection Scheme for Response Time Optimization in Cloud Computing." International Journal of Cloud Applications and Computing 11, no. 1 (2021): 93–111. http://dx.doi.org/10.4018/ijcac.2021010105.

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The quality of cloud computing services is evaluated based on various performance metrics out of which response time (RT) is most important. Nearly all cloud users demand its application's RT as minimum as possible, so to minimize overall system RT, the authors have proposed request response time prediction-based data center (DC) selection algorithm in this work. Proposed DC selection algorithm uses results of optimization function for DC selection formulated based on M/M/m queuing theory, as present cloud scenario roughly obeys M/M/m queuing model. In cloud environment, DC selection algorithm

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Tesis sobre el tema "Response Optimization algorithms"

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Lai, Ching-An. "Global optimization algorithms for adaptive infinite impulse response filters." [Gainesville, Fla.] : University of Florida, 2002. http://purl.fcla.edu/fcla/etd/UFE0000558.

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Gadiraju, Sriphani Raju. "Modified selection mechanisms designed to help evolution strategies cope with noisy response surfaces." Master's thesis, Mississippi State : Mississippi State University, 2003. http://library.msstate.edu/etd/show.asp?etd=etd-07022003-164112.

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Novieto, Divine Tuinese. "Adapting a human thermoregulation model for predicting the thermal response of older persons." Thesis, De Montfort University, 2013. http://hdl.handle.net/2086/9489.

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A human thermoregulation model has been adapted for predicting the thermal response of Typical Older Persons. The model known as the Older Persons Model predicts the core body temperature and regulatory responses of the older people in environmental exposures of cold, warm and hot. The model was developed by modifying an existing dynamic human thermoregulation model using anthropometric and thermo-physical properties of older people. The Model defines the body as two interrelating systems of the body structure (passive system) and the control system of the central nervous system (active system

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Garcia, Andrés Xavier. "Development of innovative methodologies to reduce railway rolling noise through Genetic Algorithm-based shape optimization techniques." Doctoral thesis, Universitat Politècnica de València, 2021. http://hdl.handle.net/10251/164194.

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[ES] El ruido de rodadura es un fenómeno producido debido a la interacción entre la rueda y el carril e inducido por las pequeñas irregularidades existentes en la superficie de ambos. Dichas irregularidades, conocidas como "rugosidad", provocan que se genere una vibración tanto en la rueda como el carril cuando el tren circula a una cierta velocidad, lo que consecuentemente lleva a la aparición de radiación acústica. Esto conforma una de las fuentes de molestias más relevantes y principal origen de la contaminación acústica producida por los trenes al circular por regiones urbanas densamente p

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Wan, Wen. "Semi-Parametric Techniques for Multi-Response Optimization." Diss., Virginia Tech, 2007. http://hdl.handle.net/10919/29425.

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The multi-response optimization (MRO) problem in response surface methodology (RSM) is quite common in industry and in many other areas of science. During the optimization stage in MRO, the desirability function method, one of the most flexible and popular MRO approaches and which has been utilized in this research, is a highly nonlinear function. Therefore, we have proposed use of a genetic algorithm (GA), a global optimization tool, to help solve the MRO problem. Although a GA is a very powerful optimization tool, it has a computational efficiency problem. To deal with this problem, we have

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Khalid, Adeel S. "Development and Implementation of Rotorcraft Preliminary Design Methodology using Multidisciplinary Design Optimization." Diss., Georgia Institute of Technology, 2006. http://hdl.handle.net/1853/14013.

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A formal framework is developed and implemented in this research for preliminary rotorcraft design using IPPD methodology. All the technical aspects of design are considered including the vehicle engineering, dynamic analysis, stability and control, aerodynamic performance, propulsion, transmission design, weight and balance, noise analysis and economic analysis. The design loop starts with a detailed analysis of requirements. A baseline is selected and upgrade targets are identified depending on the mission requirements. An Overall Evaluation Criterion (OEC) is developed that is used to measu

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Rich, Jonathan E. "Design Optimization Procedure for Monocoque Composite Cylinder Structures Using Response Surface Techniques." Thesis, Virginia Tech, 1997. http://hdl.handle.net/10919/35512.

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An optimization strategy for the design of composite shells is investigated. This study differs from previous work in that an advanced analysis package is utilized to provide buckling information on potential designs. The Structural Analysis of General Shells (STAGS) finite element code is used to provide linear buckling calculations for a minimum buckling load constraint. A response surface, spanning the design space, is generated from a set of design points and corresponding buckling load data. This response surface is incorporated into a genetic algorithm for optimization of composite c

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Joshi, Shirish. "Simulation-optimization studies : under efficient stimulationstrategies, and a novel response surface methodology algorithm /." Diss., This resource online, 1993. http://scholar.lib.vt.edu/theses/available/etd-06062008-170545/.

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Escobar, Roberto Luiz. "Otimização de parametros de projeto de sistemas mecanicos atraves de algoritmo genetico multi-objetivos." [s.n.], 2007. http://repositorio.unicamp.br/jspui/handle/REPOSIP/264038.

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Orientador: Katia Lucchesi Cavalca<br>Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecanica<br>Made available in DSpace on 2018-08-08T21:19:55Z (GMT). No. of bitstreams: 1 Escobar_RobertoLuiz_M.pdf: 2961640 bytes, checksum: 516985920427d6083c04c1c5a22d6470 (MD5) Previous issue date: 2007<br>Resumo: Os sistemas mecânicos são projetados para desempenhar funções específicas, e por essa razão as suas funções devem ser medidas para garantir seu desempenho dentro de uma certa precisão ou tolerância. A grande complexidade em se projetar e analisar novos projet

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Björk, Carl Johan. "PID tuning with Ant Colony Optimization (ACO) : A framework for a step response based tuning algorithm." Thesis, Mittuniversitetet, Avdelningen för elektronikkonstruktion, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-33903.

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The building automation industry lacks an affordable, simple, solution for autonomous PID controller tuning when overhead variables fluctuate. In this project, requested by Jitea AB, a solution was developed, utilising step response process modelling, numerical integration of first order differential equations, and Ant Colony Optimization (ACO). The solution was applied to two control schemes; simulated outlet flow from a virtual water tank, and the physical air pressure in the ventilation system of a preschool in Sweden. An open-loop step response provided the transfer function in each case,

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Capítulos de libros sobre el tema "Response Optimization algorithms"

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Dulikravich, George S., and Marcelo J. Colaço. "Hybrid Optimization Algorithms and Hybrid Response Surfaces." In Computational Methods in Applied Sciences. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11541-2_2.

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Sharma, Ankit Kumar, Akash Saxena, Dheeraj Kumar Palwalia, and Bhanu Pratap Soni. "An Optimal Demand Response Strategy Using Gray Wolf Optimization." In Algorithms for Intelligent Systems. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4604-8_72.

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Gandhi, Rajiv, Samir Khuller, Yoo-Ah Kim, and Yung-Chun Justin Wan. "Algorithms for Minimizing Response Time in Broadcast Scheduling." In Integer Programming and Combinatorial Optimization. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-47867-1_30.

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Sarkar, Tanmay, Molla Salauddin, Sudipta Kumar Hazra, and Runu Chakraborty. "Comparative Approach of Response Surface Methodology and Particle Swarm Optimization-Artificial Neural Network (PSO-ANN) in Rehydration Ratio Optimization for Bael (Aegle marmelos (L) Correa) Powder Production." In Algorithms for Intelligent Systems. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4087-9_17.

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Gavanelli, Marco, Maddalena Nonato, Andrea Peano, Stefano Alvisi, and Marco Franchini. "Genetic Algorithms for Scheduling Devices Operation in a Water Distribution System in Response to Contamination Events." In Evolutionary Computation in Combinatorial Optimization. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29124-1_11.

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Renu, R., Kavita Waghray, and P. Dinesh Sankar Reddy. "Optimization and Modelling of Storage Conditions in Hydro-cooling of Sapota (Manilkara zapota) with Addition of Antimicrobial Agent Using Response Surface Methodology." In Algorithms for Intelligent Systems. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-3246-4_61.

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Melin, Patricia. "Optimization of Fuzzy Response Integrators in Modular Neural Networks with Hierarchical Genetic Algorithms." In Modular Neural Networks and Type-2 Fuzzy Systems for Pattern Recognition. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-24139-0_9.

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Cavalca, Diego L., Guilherme Spavieri, and Ricardo A. S. Fernandes. "Comparative Analysis Between Particle Swarm Optimization Algorithms Applied to Price-Based Demand Response." In Artificial Intelligence and Soft Computing. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91253-0_31.

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Lopez, Miguel, Patricia Melin, and Oscar Castillo. "Optimization of Response Integration with Fuzzy Logic in Ensemble Neural Networks Using Genetic Algorithms." In Studies in Computational Intelligence. Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-70812-4_8.

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Sánchez, Daniela, Patricia Melin, Oscar Castillo, and Fevrier Valdez. "Modular Neural Networks Optimization with Hierarchical Genetic Algorithms with Fuzzy Response Integration for Pattern Recognition." In Advances in Computational Intelligence. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37798-3_22.

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Actas de conferencias sobre el tema "Response Optimization algorithms"

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Liu, Boyang, Raphael Haftka, and Mehmet Akgun. "Composite wing structural optimization using genetic algorithms and response surfaces." In 7th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization. American Institute of Aeronautics and Astronautics, 1998. http://dx.doi.org/10.2514/6.1998-4854.

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Kaul, Sudhir, and Anoop K. Dhingra. "Response Surface Algorithms for Engine Mount Optimization in Motorcycles." In ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/detc2009-86407.

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This paper presents a Response Surface Modeling (RSM) approach for solving the engine mount optimization problem for a motorcycle application. A theoretical model that captures the structural dynamics of a motorcycle engine mount system is first used to build the response surface model. The response surface model is then used to solve the engine mount optimization problem for enhanced vibration isolation. Design of Experiments (DOE), full factorial and fractional factorial formulations, are used to construct the governing experiments. Normal probability plots are used to determine the statisti

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Gharehshiran, Omid Namvar, Vikram Krishnamurthy, and George Yin. "Best-response search algorithms for non-stationary discrete stochastic optimization." In 2014 IEEE 53rd Annual Conference on Decision and Control (CDC). IEEE, 2014. http://dx.doi.org/10.1109/cdc.2014.7040042.

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Ghosh, Aritra, and Andrew Lan. "BOBCAT: Bilevel Optimization-Based Computerized Adaptive Testing." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/332.

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Computerized adaptive testing (CAT) refers to a form of tests that are personalized to every student/test taker. CAT methods adaptively select the next most informative question/item for each student given their responses to previous questions, effectively reducing test length. Existing CAT methods use item response theory (IRT) models to relate student ability to their responses to questions and static question selection algorithms designed to reduce the ability estimation error as quickly as possible; therefore, these algorithms cannot improve by learning from large-scale student response da

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Dayapule, Durga Harish, Aswin Raghavan, Prasad Tadepalli, and Alan Fern. "Emergency Response Optimization using Online Hybrid Planning." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/656.

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This paper poses the planning problem faced by the dispatcher responding to urban emergencies as a Hybrid (Discrete and Continuous) State and Action Markov Decision Process (HSA-MDP). We evaluate the performance of three online planning algorithms based on hindsight optimization for HSA- MDPs on real-world emergency data in the city of Corvallis, USA. The approach takes into account and respects the policy constraints imposed by the emergency department. We show that our algorithms outperform a heuristic policy commonly used by dispatchers by significantly reducing the average response time as

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Qi, Hongli, Tao Li, and Jing Lin. "Parameters optimization for GECDS using response surface methodology and genetic algorithms." In 2015 5th International Conference on Electronics Information and Emergency Communication (ICEIEC). IEEE, 2015. http://dx.doi.org/10.1109/iceiec.2015.7284520.

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Praga-Alejo, R. J., L. M. Torres-Trevio, and M. R. Pia-Monarrez. "Optimization Welding Process Parameters through Response Surface, Neural Network and Genetic Algorithms." In 2008 Electronics, Robotics and Automotive Mechanics Conference (CERMA). IEEE, 2008. http://dx.doi.org/10.1109/cerma.2008.70.

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Wallin, Fredrik, and Lars-Erik Eriksson. "Response Surface-Based Transition Duct Shape Optimization." In ASME Turbo Expo 2006: Power for Land, Sea, and Air. ASMEDC, 2006. http://dx.doi.org/10.1115/gt2006-90978.

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Demands on improved efficiency and reduced noise levels cause a strive toward very high by-pass ratio (BPR) turbo-fan-engines resulting in large fans and small high-pressure-ratio cores. The trend of increasing the radial offset between low- and high-pressure systems has made the design of intermediate transition ducts an area of growing importance. Shape optimization techniques for turbo-machinery applications have become a powerful aero-design tool and thanks to the rapid development of computer technology, computational fluid dynamics (CFD) may be used for optimization purposes. Surrogate m

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Bakker, C., G. T. Parks, and J. P. Jarrett. "Optimization Algorithms and ODE’s in MDO." In ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/detc2013-12146.

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There is a need for a stronger theoretical understanding of Multidisciplinary Design Optimization (MDO) within the field. Having developed a differential geometry framework in response to this need, we consider how standard optimization algorithms can be modeled using systems of ordinary differential equations (ODEs) while also reviewing optimization algorithms which have been derived from ODE solution methods. We then use some of the framework’s tools to show how our resultant systems of ODEs can be analyzed and their behaviour quantitatively evaluated. In doing so, we demonstrate the power a

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Jolly, L., M. A. Jabbar, and Q. Liu. "Design optimization of permanent magnet motors using response surface methodology and genetic algorithms." In INTERMAG Asia 2005: Digest of the IEEE International Magnetics Conference. IEEE, 2005. http://dx.doi.org/10.1109/intmag.2005.1463474.

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Informes sobre el tema "Response Optimization algorithms"

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Apostolatos, A., B. Keith, C. Soriano, and R. Rossi. D6.1 Deterministic optimization software. Scipedia, 2021. http://dx.doi.org/10.23967/exaqute.2021.2.018.

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This deliverable focuses on the implementation of deterministic optimization algorithms and problem solvers within KRATOS open-source software. One of the main challenges of optimization algorithms in Finite-Element based optimization is how to get the gradient of response functions which are used as objective and constraints when this is not available in an explicit form. The idea is to use local sensitivity analysis to get the gradient of the response function(s)

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