Academic literature on the topic 'Multi-objective Design'
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Journal articles on the topic "Multi-objective Design"
Min, Xinyuan, Jaap Sok, Feije de Zwart, and Alfons Oude Lansink. "Multi-stakeholder multi-objective greenhouse design optimization." Agricultural Systems 215 (March 2024): 103855. http://dx.doi.org/10.1016/j.agsy.2024.103855.
Full textFreier, Lars, and Eric von Lieres. "Robust multi-objective process design." New Biotechnology 33 (July 2016): S27. http://dx.doi.org/10.1016/j.nbt.2016.06.822.
Full textSun, Qi, Tinghuan Chen, Siting Liu, Jianli Chen, Hao Yu, and Bei Yu. "Correlated Multi-objective Multi-fidelity Optimization for HLS Directives Design." ACM Transactions on Design Automation of Electronic Systems 27, no. 4 (July 31, 2022): 1–27. http://dx.doi.org/10.1145/3503540.
Full textYAMASHINA, Hajime, Susumu OKUMURA, and Yoshimasa KONDO. "Parameter Design with Multi Objective Characteristics." Journal of the Japan Society for Precision Engineering 58, no. 3 (1992): 516–20. http://dx.doi.org/10.2493/jjspe.58.516.
Full textKor, Jean, Xiang Chen, Zhizhong Sun, and Henry Hu. "Casting Design Through Multi-Objective Optimization." IFAC Proceedings Volumes 44, no. 1 (January 2011): 11642–47. http://dx.doi.org/10.3182/20110828-6-it-1002.01726.
Full textJoseph, Shaine, Hyung W. Kang, and Uday K. Chakraborty. "Lens design as multi-objective optimisation." International Journal of Automation and Control 5, no. 3 (2011): 189. http://dx.doi.org/10.1504/ijaac.2011.042851.
Full textSanchis, J., M. Martinez, and X. Blasco. "Multi-objective engineering design using preferences." Engineering Optimization 40, no. 3 (March 2008): 253–69. http://dx.doi.org/10.1080/03052150701693057.
Full textEckert, Jony Javorski, Fabio Mazzariol Santiciolli, Ludmila C. A. Silva, and Franco Giuseppe Dedini. "Vehicle drivetrain design multi-objective optimization." Mechanism and Machine Theory 156 (February 2021): 104123. http://dx.doi.org/10.1016/j.mechmachtheory.2020.104123.
Full textPelinescu, Diana M., and Michael Yu Wang. "Multi-objective optimal fixture layout design." Robotics and Computer-Integrated Manufacturing 18, no. 5-6 (October 2002): 365–72. http://dx.doi.org/10.1016/s0736-5845(02)00027-3.
Full textLim, Dudy, Yew-Soon Ong, Yaochu Jin, Bernhard Sendhoff, and Bu Sung Lee. "Inverse multi-objective robust evolutionary design." Genetic Programming and Evolvable Machines 7, no. 4 (September 16, 2006): 383–404. http://dx.doi.org/10.1007/s10710-006-9013-7.
Full textDissertations / Theses on the topic "Multi-objective Design"
Kipouros, Timoleon. "Multi-objective aerodynamic design optimisation." Thesis, University of Cambridge, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.614261.
Full textNezhadali, Vaheed. "Multi-objective optimization of Industrial robots." Thesis, Linköpings universitet, Maskinkonstruktion, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-113283.
Full textLiu, Wei. "A multi-objective approach for RMT design." Thesis, University of Ottawa (Canada), 2006. http://hdl.handle.net/10393/27149.
Full textLi, Yinjiang. "Robust multi-objective optimisation in electromagnetic design." Thesis, University of Southampton, 2017. https://eprints.soton.ac.uk/415498/.
Full textRamadan, Saleem Z. "Bayesian Multi-objective Design of Reliability Testing." Ohio University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1298474937.
Full textEl-Sayed, Jacqueline Johnson. "Multi-objective optimization of manufacturing processes design /." free to MU campus, to others for purchase, 1997. http://wwwlib.umi.com/cr/mo/fullcit?p9841282.
Full textFaragalli, Michele. "Multi-objective design optimization of compliant lunar wheels." Thesis, McGill University, 2013. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=117030.
Full textLe développement de la roue treillis métallique de l'Apollo Lunar Roving Vehicle a été réalisé par un processus d'essais et d'erreurs. Les récents développements de roues flexibles, motivé par un regain d'intérêt pour l'exploration lunaire, ont maintenant à leur disposition des outils de simulation numérique plus sophistiqués. Cependant, la majorité des chercheurs emploient toujours des méthodes expérimentales ou paramétriques pour développer leurs roues. Cette thèse propose une nouvelle approche systématique pour l'optimisation de concepts de roues lunaires flexibles. Le problème est décomposé en deux analyses se rapportant au niveau du système et celui des composantes. L'analyse au niveau du système étudie l'effet du comportement de la roue élastique sur des mesures de performance lors d'une mission du rover. Ceci est réalisé en optimisant les paramètres décrivant une roue flexible à l'aide de modèles multidisciplinaires. Différents concepts de roues sont explorés à l'aide de prototypes et d'essais physiques, ainsi que de modélisations numériques. La performance de chacun des concepts de roues flexibles cellulaires, iRings et segmentés sont comparées à un pneu standard. L'analyse au niveau des composantes effectue une optimisation multi-objective afin de déterminer, par le biais de simulations numériques, le concept optimal de roues flexibles cellulaires. L'efficacité de la méthodologie pour optimiser la roue cellulaire est ensuite vérifiée et les limites de cette approche sont examinées en détail. Finalement, une discussion sur l'application de la méthodologie proposée à des concepts de roues arbitraires est abordée.
Skinner, Benjamin Adam. "Multi-objective evolutionary optimisation of submarine propulsion design." Thesis, University of Cambridge, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.611230.
Full textBrown, Nathan C. (Nathan Collin). "Early building design using multi-objective data approaches." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/123573.
Full textCataloged from PDF version of thesis.
Includes bibliographical references (pages 201-219).
During the design process in architecture, building performance and human experience are increasingly understood through computation. Within this context, this dissertation considers how data science and interactive optimization techniques can be combined to make simulation a more effective component of a natural early design process. It focuses on conceptual design, since technical principles should be considered when global decisions are made concerning the massing, structural system, and other design aspects that affect performance. In this early stage, designers might simulate structure, energy, daylighting, thermal comfort, acoustics, cost, and other quantifiable objectives. While parametric simulations offer the possibility of using a design space exploration framework to make decisions, their resulting feedback must be synthesized together, along with non-quantifiable design goals.
Previous research has developed optimization strategies to handle such multi-objective scenarios, but opportunities remain to further adapt optimization for the creative task of early building design, including increasing its interactivity, flexibility, accessibility, and ability to both support divergent brainstorming and enable focused performance improvement. In response, this dissertation proposes new approaches to parametric design space formulation, interactive optimization, and diversity-based design. These methods span in utility from early ideation, through global design exploration, to local exploration and optimization. The first presented technique uses data science methods to interrogate, transform, and, for specific cases, generate design variables for exploration. The second strategy involves interactive stepping through a design space using estimated gradient information, which offers designers more freedom compared to automated solvers during local exploration.
The third method addresses computational measurement of diversity within parametric design and demonstrates how such measurements can be integrated into creative design processes. These contributions are demonstrated on an integrated early design example and preliminarily validated using a design study that provides feedback on the habits and preferences of architects and engineers while engaging with data-driven tools. This study reveals that performance-enabled environments tend to improve simulated design objectives, while designers prefer more flexibility than traditional automated optimization approaches when given the choice. Together, these findings can stimulate further development in the integration of interactive approaches to multi-objective early building design. Key words: design space exploration, conceptual design, design tradeoffs, interactive design tools, structural design, sustainable design, multi-objective optimization, data science, surrogate modeling
by Nathan C. Brown.
Ph. D. in Architecture: Building Technology
Ph.D.inArchitecture:BuildingTechnology Massachusetts Institute of Technology, Department of Architecture
Paik, Sangwook. "Multi-objective optimal design of steel trusses in unstructured design domains." Thesis, Texas A&M University, 2005. http://hdl.handle.net/1969.1/3124.
Full textBooks on the topic "Multi-objective Design"
Liu, Aying. A multi-objective and multi-design evaluation procedure for environmental protection forestry. Portsmouth: University of Portsmouth, Department of Economics, 1997.
Find full textWang, Lihui, Amos H. C. Ng, and Kalyanmoy Deb, eds. Multi-objective Evolutionary Optimisation for Product Design and Manufacturing. London: Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-652-8.
Full textSilvano, Cristina, William Fornaciari, and Eugenio Villar, eds. Multi-objective Design Space Exploration of Multiprocessor SoC Architectures. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-8837-9.
Full textC, Ng Amos H., Deb Kalyanmoy, and SpringerLink (Online service), eds. Multi-objective Evolutionary Optimisation for Product Design and Manufacturing. London: Springer-Verlag London Limited, 2011.
Find full textUnited States. National Aeronautics and Space Administration., ed. Multi-objective decision-making under uncertainty: Fuzzy logic methods. [Washington, DC]: National Aeronautics and Space Administration, 1994.
Find full textUnited States. National Aeronautics and Space Administration., ed. Multi-objective decision-making under uncertainty: Fuzzy logic methods. [Washington, DC]: National Aeronautics and Space Administration, 1994.
Find full textS, Rao S. Applications of fuzzy theories to multi-objective system optimization. Moffett Field, Calif: National Aeronautics and Space Administration, Ames Research Center, 1991.
Find full textCenter, Lewis Research, and United States. National Aeronautics and Space Administration., eds. Multi objective controller design for linear systems via optimal interpolation. [Columbus, Ohio]: Ohio State University, 1996.
Find full textCenter, Lewis Research, and United States. National Aeronautics and Space Administration., eds. Multi objective controller design for linear systems via optimal interpolation. [Columbus, Ohio]: Ohio State University, 1996.
Find full textSaravanos, D. A. Multi-objective shape and material optimization of composite structures including damping. [Washington, D.C.]: NASA, 1990.
Find full textBook chapters on the topic "Multi-objective Design"
Han, Xu, and Jie Liu. "Micro Multi-objective Genetic Algorithm." In Numerical Simulation-based Design, 153–78. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-10-3090-1_9.
Full textChen, Yi, and Yun Li. "Extra‐Numerical Multi‐Objective optimization." In Computational Intelligence Assisted Design, 115–23. Boca Raton, FL : CRC Press, Taylor & Francis Group, 2018. | "A science publishers book.": CRC Press, 2018. http://dx.doi.org/10.1201/9781315153179-8.
Full textSun, Jian-Qiao, Fu-Rui Xiong, Oliver Schütze, and Carlos Hernández. "Multi-objective Optimal Control Design." In Cell Mapping Methods, 149–68. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0457-6_10.
Full textSun, Jian-Qiao, Fu-Rui Xiong, Oliver Schütze, and Carlos Hernández. "Multi-objective Optimal Structure Design." In Cell Mapping Methods, 169–90. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0457-6_11.
Full textSun, Jian-Qiao, Fu-Rui Xiong, Oliver Schütze, and Carlos Hernández. "Multi-objective Optimal Airfoil Design." In Cell Mapping Methods, 191–202. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0457-6_12.
Full textHan, Xu, and Jie Liu. "Introduction to Multi-objective Optimization Design." In Numerical Simulation-based Design, 141–51. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-10-3090-1_8.
Full textParmee, Ian C. "Multi-objective Satisfaction and Optimisation." In Evolutionary and Adaptive Computing in Engineering Design, 177–203. London: Springer London, 2001. http://dx.doi.org/10.1007/978-1-4471-0273-1_10.
Full textJerin Leno, I., S. Saravana Sankar, and S. G. Ponnambalam. "Multi Objective Integrated Layout Design Problem." In Swarm, Evolutionary, and Memetic Computing, 500–508. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35380-2_59.
Full textD’Errico, Fabrizio. "Multi-Objective Optimization in Engineering Design." In SpringerBriefs in Materials, 33–67. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-13030-9_2.
Full textM’laouhi, Ibrahim, Najeh Ben Guedria, and Hichem Smaoui. "Multi-objective Discrete Rotor Design Optimization." In Condition Monitoring of Machinery in Non-Stationary Operations, 193–200. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28768-8_20.
Full textConference papers on the topic "Multi-objective Design"
Liu, Yiwei, Yiping Liu, Jiahao Yang, Xinyi Zhang, Li Wang, and Xiangxiang Zeng. "Multi-Objective Molecular Design in Constrained Latent Space." In 2024 International Joint Conference on Neural Networks (IJCNN), 1–8. IEEE, 2024. http://dx.doi.org/10.1109/ijcnn60899.2024.10651509.
Full textJian, Huang, and Wang Yihan. "Asset Optimization Scheme Design with Multi-Objective Optimization." In 2024 IEEE International Conference on Information Technology, Electronics and Intelligent Communication Systems (ICITEICS), 1–5. IEEE, 2024. http://dx.doi.org/10.1109/iciteics61368.2024.10625611.
Full textWen, Yi, Wei Ye, and Gang Yu. "A Hybrid Multi-objective Model for Multi-story Warehouse Design: A Case Study in Shenzhen." In CAADRIA 2024: Accelerated Design, 283–92. CAADRIA, 2024. http://dx.doi.org/10.52842/conf.caadria.2024.1.283.
Full textZangl, H., and G. Steiner. "Optimal design of multi-objective multi-sensor systems." In Proceedings of the 2005 IEEE International Workshop on Advanced Methods for Uncertainty Estimation in Measurement. IEEE, 2005. http://dx.doi.org/10.1109/amuem.2005.1594616.
Full textYuan-Chang Chang, Li-Wei Kuo, and Jenq-Lang Wu. "Reliable multi-objective decentralized controller design." In 2010 International Conference on System Science and Engineering (ICSSE). IEEE, 2010. http://dx.doi.org/10.1109/icsse.2010.5551749.
Full textWang, Wei, Xin-long Chang, You-hong Zhang, and Chun-wen Wang. "Composite Laminated Multi-Objective Optimization Design." In 2020 International Conference on Artificial Intelligence and Electromechanical Automation (AIEA). IEEE, 2020. http://dx.doi.org/10.1109/aiea51086.2020.00134.
Full textKeough, Ian, and David Benjamin. "Multi-objective optimization in architectural design." In the 2010 Spring Simulation Multiconference. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1878537.1878736.
Full textRojas, José David, and Victor M. Alfaro. "Multi-objective design of industrial controllers." In 2017 IEEE 3rd Colombian Conference on Automatic Control (CCAC). IEEE, 2017. http://dx.doi.org/10.1109/ccac.2017.8320344.
Full textKor, Jean, Xiang Chen, Zhizhong Sun, and Henry Hu. "Casting Design through Multi-objective Optimization." In 2009 Second International Conference on Future Information Technology and Management Engineering (FITME). IEEE, 2009. http://dx.doi.org/10.1109/fitme.2009.156.
Full textPoian, M., S. Poles, F. Bernasconi, E. Leroux, W. Steffe, and M. Zolesi. "Multi-objective optimization for antenna design." In 2008 IEEE International Conference on Microwaves, Communications, Antennas and Electronic Systems (COMCAS). IEEE, 2008. http://dx.doi.org/10.1109/comcas.2008.4562817.
Full textReports on the topic "Multi-objective Design"
Kuprowicz, Nicholas J. The Integrated Multi-Objective Multi-Disciplinary Jet Engine Design Optimization Program. Fort Belvoir, VA: Defense Technical Information Center, January 1999. http://dx.doi.org/10.21236/ada372032.
Full textFernandez, Ruben, Hernando Lugo, and Georfe Dulikravich. Aerodynamic Shape Multi-Objective Optimization for SAE Aero Design Competition Aircraft. Florida International University, October 2021. http://dx.doi.org/10.25148/mmeurs.009778.
Full textWenren, Yonghu, Joon Lim, Luke Allen, Robert Haehnel, and Ian Dettwiler. Helicopter rotor blade planform optimization using parametric design and multi-objective genetic algorithm. Engineer Research and Development Center (U.S.), December 2022. http://dx.doi.org/10.21079/11681/46261.
Full textDulikravich, George S., Igor N. Egorov, Vinod K. Sikka, and G. Muralidharan. Alloys-by-Design Strategies Using Stochastic Multi-Objective Optimization: Initial Formulation and Results. Fort Belvoir, VA: Defense Technical Information Center, January 2003. http://dx.doi.org/10.21236/ada416083.
Full textBau, Domenico. Recovery Act: Multi-Objective Optimization Approaches for the Design of Carbon Geological Sequestration Systems. Office of Scientific and Technical Information (OSTI), May 2013. http://dx.doi.org/10.2172/1097612.
Full textBarlow, Gregory J. Design of Autonomous Navigation Controllers for Unmanned Aerial Vehicles Using Multi-Objective Genetic Programming. Fort Belvoir, VA: Defense Technical Information Center, March 2004. http://dx.doi.org/10.21236/ada460111.
Full textKobayashi, Marcelo H. (HBCU) Development and Application of a Biologically Inspired Methodology for the Optimized, Multi-Disciplinary and Multi-Objective Design of Air Vehicles. Fort Belvoir, VA: Defense Technical Information Center, May 2013. http://dx.doi.org/10.21236/ada584389.
Full textChoi, Yong-Joon, Mohammad M Mostafa Abdo, Yong-Joon Choi, Juan Luque Gutierrez, Jason Hou, Christoper Gosdin, and Jarrett Valeri. Pressurized-Water Reactor Core Design Demonstration with Genetic Algorithm Based Multi-Objective Plant Fuel Reload Optimization Platform. Office of Scientific and Technical Information (OSTI), September 2023. http://dx.doi.org/10.2172/2006453.
Full textChoi, Yong-Joon, Junyung Kim, Mohammad M Mostafa Abdo, Juan Luque Gutierrez, Jason Hou, Christoper Gosdin, and Jarrett Valeri. Pressurized-Water Reactor Core Design Demonstration with Genetic Algorithm Based Multi-Objective Plant Fuel Reload Optimization Platform. Office of Scientific and Technical Information (OSTI), September 2023. http://dx.doi.org/10.2172/2006437.
Full textAllen, Luke, Joon Lim, Robert Haehnel, and Ian Dettwiller. Helicopter rotor blade multiple-section optimization with performance. Engineer Research and Development Center (U.S.), June 2021. http://dx.doi.org/10.21079/11681/41031.
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