Academic literature on the topic 'Multi-criteria Design'
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Journal articles on the topic "Multi-criteria Design"
Radeva, Irina. "Multi-Criteria Models for Clusters Design." Cybernetics and Information Technologies 13, no. 1 (March 1, 2013): 18–33. http://dx.doi.org/10.2478/cait-2013-0003.
Full textMohamed, Nejlaoui, Najlawi Bilel, and Ali Sulaiman Alsagri. "A multi-objective methodology for multi-criteria engineering design." Applied Soft Computing 91 (June 2020): 106204. http://dx.doi.org/10.1016/j.asoc.2020.106204.
Full textZargaryan, Yu A., E. V. Zargaryan, I. A. Dmitrieva, O. N. Sakharova, and I. V. Pushnina. "Modeling design information systems with multi-criteria." Journal of Physics: Conference Series 1679 (November 2020): 032057. http://dx.doi.org/10.1088/1742-6596/1679/3/032057.
Full textSerafini, Marco, Davide Russo, and Caterina Rizzi. "Multi Criteria Material Selection for Eco-design." Computer-Aided Design and Applications 12, no. 5 (March 9, 2015): 526–36. http://dx.doi.org/10.1080/16864360.2015.1014730.
Full textSirisalee, P., M. F. Ashby, G. T. Parks, and P. J. Clarkson. "Multi-Criteria Material Selection in Engineering Design." Advanced Engineering Materials 6, no. 12 (February 5, 2004): 84–92. http://dx.doi.org/10.1002/adem.200300554.
Full textBeck, James L., Eduardo Chan, Ayhan Irfanoglu, and Costas Papadimitriou. "Multi-criteria optimal structural design under uncertainty." Earthquake Engineering & Structural Dynamics 28, no. 7 (July 1999): 741–61. http://dx.doi.org/10.1002/(sici)1096-9845(199907)28:7<741::aid-eqe840>3.0.co;2-6.
Full textKuan, Yong, and Yahaya Ahmad. "Architectural Design Criteria for Multi-Storey Housing Buildings." Open House International 41, no. 1 (March 1, 2016): 67–73. http://dx.doi.org/10.1108/ohi-01-2016-b0009.
Full textGeldermann, Jutta, Nils Lerche, and Juan David Sepulveda. "Combining multi-criteria decision analysis and design thinking." European J. of Industrial Engineering 12, no. 5 (2018): 708. http://dx.doi.org/10.1504/ejie.2018.094597.
Full textGeldermann, Jutta, Juan David Sepulveda, and Nils Lerche. "Combining multi-criteria decision analysis and design thinking." European J. of Industrial Engineering 12, no. 5 (2018): 708. http://dx.doi.org/10.1504/ejie.2018.10015684.
Full textPapakostas, N., G. Pintzos, C. Giannoulis, N. Nikolakis, and G. Chryssolouris. "Multi-criteria Assembly Line Design under Demand Uncertainty." Procedia CIRP 25 (2014): 86–92. http://dx.doi.org/10.1016/j.procir.2014.10.015.
Full textDissertations / Theses on the topic "Multi-criteria Design"
Anil, Kivanc Ali. "Multi-criteria analysis in Naval Ship Design /." Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2005. http://library.nps.navy.mil/uhtbin/hyperion/05Mar%5FAnil.pdf.
Full textThesis Advisor(s): Fotis Papoulias, Roman B. Statnikov. Includes bibliographical references (p. 241). Also available online.
Sirisalee, Pasu. "Multi-criteria material selection in engineering design." Thesis, University of Cambridge, 2005. https://www.repository.cam.ac.uk/handle/1810/251967.
Full textTreitz, Martin. "Production process design using multi-criteria analysis." Karlsruhe : Univ.-Verl. Karlsruhe, 2006. http://www.uvka.de/univerlag/volltexte/2006/178/.
Full textAnil, Kivanc A. "Multi-criteria analysis in naval ship design." Thesis, Monterey California. Naval Postgraduate School, 2005. http://hdl.handle.net/10945/2325.
Full textNumerous optimization problems involve systems with multiple and often contradictory criteria. Such contradictory criteria have been an issue for marine/naval engineering design studies for many years. This problem becomes more important when one considers novel ship types with very limited or no operational record. A number of approaches have been proposed to overcome these multiple criteria design optimization problems. This Thesis follows the Parameter Space Investigation (PSI) technique to address these problems. The PSI method is implemented with a software package called MOVI (Multi-criteria Optimization and Vector Identification). Two marine/naval engineering design optimization models were investigated using the PSI technique along with the MOVI software. The first example was a bulk carrier design model which was previously studied with other optimization methods. This model, which was selected due to its relatively small dimensionality and the availability of existing studies, was utilized in order to demonstrate and validate the features of the proposed approach. A more realistic example was based on the "MIT Functional Ship Design Synthesis Model" with a greater number of parameters, criteria, and functional constraints. A series of optimization studies conducted for this model demonstrated that the proposed approach can be implemented in a naval ship design environment and can lead to a large design parameter space exploration with minimum computational effort.
Lieutenant Junior Grade, Turkish Navy
Kudikala, Rajesh. "System architecture design using multi-criteria optimization." Thesis, University of Sheffield, 2015. http://etheses.whiterose.ac.uk/9703/.
Full textHodgett, Richard Edgar. "Multi-criteria decision-making in whole process design." Thesis, University of Newcastle Upon Tyne, 2013. http://hdl.handle.net/10443/1838.
Full textCortes, Quiroz C. A. "Design, analysis and multi-criteria optimization of micromixers." Thesis, University College London (University of London), 2012. http://discovery.ucl.ac.uk/1357309/.
Full textBouzembrak, Yamine. "Multi-criteria Supply Chain Network Design under uncertainty." Thesis, Artois, 2011. http://www.theses.fr/2011ARTO0211/document.
Full textThis thesis contributes to the debate on how uncertainty and concepts of sustainable development can be put into modern supply chain network and focuses on issues associated with the design of multi-criteria supply chain network under uncertainty. First, we study the literature review , which is a review of the current state of the art of Supply Chain Network Design approaches and resolution methods. Second, we propose a new methodology for multi-criteria Supply Chain Network Design (SCND) as well as its application to real Supply Chain Network (SCN), in order to satisfy the customers demand and respect the environmental, social, legislative, and economical requirements. The methodology consists of two different steps. In the first step, we use Geographic Information System (GIS) and Analytic Hierarchy Process (AHP) to buildthe model. Then, in the second step, we establish the optimal supply chain network using Mixed Integer Linear Programming model (MILP). Third, we extend the MILP to a multi-objective optimization model that captures a compromisebetween the total cost and the environment influence. We use Goal Programming approach seeking to reach the goals placed by Decision Maker. After that, we develop a novel heuristic solution method based on decomposition technique, to solve large scale supply chain network design problems that we failed to solve using exact methods. The heuristic method is tested on real case instances and numerical comparisons show that our heuristic yield high quality solutions in very limited CPU time. Finally, again, we extend the MILP model presented before where we assume that the costumer demands are uncertain. We use two-stage stochastic programming approach to model the supply chain network under demand uncertainty. Then, we address uncertainty in all SC parameters: opening costs, production costs, storage costs and customers demands. We use possibilistic linear programming approach to model the problem and we validate both approaches in a large application case
Sánchez, Corrales Helem Sabina. "Multi-objective optimization and multicriteria design of PI /PID controllers." Doctoral thesis, Universitat Autònoma de Barcelona, 2016. http://hdl.handle.net/10803/393990.
Full textNowadays, the proportional integral and proportional integral derivatives are the most used control algorithm in the industry. Moreover, the fractional controllers have received attention recently for both, the research community and from the industrial point of view. Owing to this, in this thesis some of the scenarios involve the tuning of these controllers by using the Multiobjective Optimization Design procedure. This procedure focuses on providing reasonable trade-off among the conflictive objectives and brings the designer the possibility to appreciate the comparison of the design objectives. This thesis is divided in three parts. The first part, presented the fundamentals of the control system showing and discussing the different trade-offs between performance/robustness and servo/regulation operation modes. On the other hand a background on multi-objective optimization has been provided. The second part, introduces the Nash solution as a multi-criteria decision making technique, to select a point from the Pareto front that represent the best compromise among the design objective. This solution provides a semi-automatic selection from the Pareto front approximation and offers a good trade-off between the goal objectives. Hereafter, a Multi-stage approach for the multi-objective optimization process is presented. This approach involves two algorithms: a deterministic and evolutionary algorithm. In which both algorithms complement each other in despite of their drawbacks and improve the results of the overall optimization in terms of convergence and accuracy. Further, the introduction of reliability based objective into the multi-objective problem is carried out, to measure the performance degradation. It is worthwhile to mention that, due to the existence of uncertainties in real-world designing and manufacturing having this design objective will give another perspective to the designer. In order to validate the approach, two different case studies has been considered, the Boiler control problem for controller tuning and as second case, a non-linear Peltier Cell. Finally, the third part of this thesis, the contributions on controller tuning have been presented. First, a set of tuning rules based on the NS for a proportional-integral (PI) controller have been devised, where the robustness/performance trade-off have been considered. Moreover, as a second case it is presented a tuning for proportional-integral-derivative controller where the trade-off of the performance/robustness and servo/regulation operation mode has been considered. Moreover, the fractional-order-proportional-integral-derivative controller is tuned by using the Multi-stage approach for the MOO process.
Andresen, Inger. "A Multi-Criteria Decision-Making Method for Solar Building Design." Doctoral thesis, Norwegian University of Science and Technology, Faculty of Architecture and Fine Art, 2000. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-451.
Full textThe background for this thesis is based on the assumption that the success of solar buildings relies on the assessment and integration of all the different design objectives, called criteria. These criteria are often quite complicated to deal with (e.g. environmental loading) and may be conflicting. The different design issues and the many different available energy technologies call for different areas of expertise to be involved in the design of solar buildings. This makes it difficult to evaluate the overall “goodness” of a proposed design solution. Also, the communication between design professionals and the client becomes complicated.
The goal of this work was therefore to produce a means for the design team and clients to be able to better understand and handle holistic solar design. A first hypothesis was that a structured approach for evaluating design alternatives might be a means to this end.
In order to specify an approach that would fit into the building design process, an analysis of design process theory and building design practice was carried out (chapter 2). Also, special solar design issues were investigated. This analysis resulted in the following conclusions:
· Most building design processes start out with no clearly defined goals or criteria of success. The design criteria are refined and discovered through evaluation and feedback on alternative design proposals.
· Design involves a lot of subjective value judgements, and decisions are often based on experience, “gut feeling”, or intuition. Design options are evaluated based on quantitative and qualitative performance measures. There exists no objective optimal design solution.
· It is possible to identify some main activities that are common to most design processes. These are categorized into 4 main tasks: problem formulation, generation of alternatives, performance prediction and evaluation. The activities are very much overlapping and dependent on each other.
· Decision-making in design happens mainly through evaluation of proposed design solutions.
Books on the topic "Multi-criteria Design"
Velimirović, Lazar Z., Aleksandar Janjić, and Jelena D. Velimirović. Multi-criteria Decision Making for Smart Grid Design and Operation. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-7677-3.
Full textNguyen, Van Thanh Tien, Nhut T. M. Vo, Van Chinh Truong, and Van-Thuc Nguyen. Multi-Criteria Decision-Making and Optimum Design with Machine Learning. Boca Raton: CRC Press, 2024. http://dx.doi.org/10.1201/9781032635170.
Full textSimms, Christine J. Process optimisation using design of experiments and some of the principles of Taguchi: Resolving multi-criteria conflicts within parameter design in static and dynamic processes. [S.l: The author], 2002.
Find full textKlein, Donald E. Analysis, design, and implementation of a web-based training system for multi-criteria decision support, integrating hypertext, multimedia-based case studies and training software. Monterey, Calif: Naval Postgraduate School, 1997.
Find full textSindhwani, Rahul. Multi-Criteria Decision Modelling. Taylor & Francis Group, 2021.
Find full textD’Errico, Fabrizio. Material Selections by a Hybrid Multi-Criteria Approach. Springer, 2015.
Find full textD'Errico, Fabrizio. Material Selections by a Hybrid Multi-Criteria Approach. Springer, 2015.
Find full textAkgül, Yakup, and Kemal Vatansever. Multi-Criteria Decision-Making Models for Website Evaluation. IGI Global, 2019.
Find full textAkgül, Yakup, and Kemal Vatansever. Multi-Criteria Decision-Making Models for Website Evaluation. IGI Global, 2019.
Find full textDavim, J. Paulo, Rahul Sindhwani, Punj Lata Singh, Bhawna Kumar, and Varinder Kumar Mittal. Multi-Criteria Decision Modelling: Applicational Techniques and Case Studies. Taylor & Francis Group, 2021.
Find full textBook chapters on the topic "Multi-criteria Design"
Bestle, D., and P. Eberhard. "Multi–Criteria Multi–Model Design Optimization." In IUTAM Symposium on Optimization of Mechanical Systems, 33–40. Dordrecht: Springer Netherlands, 1996. http://dx.doi.org/10.1007/978-94-009-0153-7_5.
Full textDelinchant, Benoit, Laurence Estrabaud, Laurent Gerbaud, and Frédéric Wurtz. "Multi-Criteria Design and Optimization Tools." In Integrated Design by Optimization of Electrical Energy Systems, 193–245. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118561812.ch5.
Full textWillmes, Lars, and Thomas Bäck. "Multi-criteria Airfoil Design with Evolution Strategies." In Lecture Notes in Computer Science, 782–95. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-36970-8_55.
Full textBertoni, Marco. "Multi Criteria Decision Making for PSS Design." In Data-Driven Decision Making for Product Service Systems, 87–113. Cham: Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-60082-1_4.
Full textNguyen, Hung T., and Vladik Kreinovich. "Multi-Criteria Optimization: An Important Foundation of Fuzzy System Design." In Fuzzy Systems Design, 24–35. Heidelberg: Physica-Verlag HD, 1998. http://dx.doi.org/10.1007/978-3-7908-1885-7_2.
Full textLavagna, Michelle, and Amalia Ercoli Finzi. "Spacecraft Design as a Multi-Criteria Decision-Making." In Applied Optimization, 57–83. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/978-1-4757-3752-3_5.
Full textWoźniak, Piotr. "Multi-objective Control Systems Design with Criteria Reduction." In Lecture Notes in Computer Science, 583–87. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-17298-4_65.
Full textMahammed, Nadir, and Sidi Mohamed Benslimane. "Toward Multi Criteria Optimization of Business Processes Design." In Model and Data Engineering, 98–107. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-45547-1_8.
Full textBazargan-Lari, Massoud. "A Multi-Criteria Model for Warehouse Layout Design." In Lecture Notes in Economics and Mathematical Systems, 327–37. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-642-56680-6_30.
Full textMunier, Nolberto, Eloy Hontoria, and Fernando Jiménez-Sáez. "Design of a Decision-Making Model Reality-Wise: How Should It Be Done?" In Strategic Approach in Multi-Criteria Decision Making, 81–98. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-02726-1_5.
Full textConference papers on the topic "Multi-criteria Design"
Montagna, Giaime Niccolò, Simone Piccardo, Matteo Passalacqua, Daria Bellotti, Luca Mantelli, and Massimo Rivarolo. "THE ENERGY SYSTEMS ANALYSIS WITH A MULTI-CRITERIA DESIGN TOOL TO DECARBONIZE MARITIME TRANSPORT." In 37th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 2024), 216–27. Zografos, Greece: ECOS 2024, 2024. http://dx.doi.org/10.52202/077185-0019.
Full textDrid, Hamza, Bernard Cousin, Samer Lahoud, and Miklos Molnar. "Multi-criteria p-cycle network design." In 2008 33rd IEEE Conference on Local Computer Networks (LCN 2008). IEEE, 2008. http://dx.doi.org/10.1109/lcn.2008.4664191.
Full textShiozawa, Kazufumi, Taiki Kimura, Tetsuaki Matsunawa, Shigeki Nojima, and Toshiya Kotani. "Multi-criteria hotspot detection using pattern classification." In Design-Process-Technology Co-optimization for Manufacturability XIII, edited by Jason P. Cain and Chi-Min Yuan. SPIE, 2019. http://dx.doi.org/10.1117/12.2515665.
Full textSemenishchev, Evgeny, Igor Shraifel, Vladimir Marchuk, Ilia Svirin, and Sergei Makov. "A multi-criteria method for noise reduction." In 2016 IEEE East-West Design & Test Symposium (EWDTS). IEEE, 2016. http://dx.doi.org/10.1109/ewdts.2016.7807651.
Full textSem, K., and S. Malhotra. "Multi-criteria network design using genetic algorithm." In IET Conference on Wireless, Mobile and Multimedia Networks. IEE, 2008. http://dx.doi.org/10.1049/cp:20080144.
Full textSerafini, Marco, Davide Russon, and Caterina Rizzi. "Multi Criteria Material Selection for Eco-design." In CAD'14. CAD Solutions LLC, 2014. http://dx.doi.org/10.14733/cadconfp.2014.129-130.
Full textSerafni, Marco. "Multi Criteria Material Selection for Eco-design." In CAD'14 Hong Kong. CAD Solutions LLC, 2014. http://dx.doi.org/10.14733/cadconfp.2014.132-134.
Full textUnal, Ramazan, Gullu Kiziltas, and Volkan Patoglu. "Multi-criteria Design Optimization of Parallel Robots." In 2008 IEEE Conference on Robotics, Automation and Mechatronics (RAM). IEEE, 2008. http://dx.doi.org/10.1109/ramech.2008.4681427.
Full textAlexopoulos, K., M. Pappas, V. Karabatsou, D. Mavrikios, and G. Chryssolouris. "Human Motion Adaptation: A Multi-Criteria Approach." In 2006 Digital Human Modeling for Design and Engineering Conference. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2006. http://dx.doi.org/10.4271/2006-01-2351.
Full textYeung, S. H., K. F. Man, and W. S. Chan. "ISM Band Antenna Design Based on Fuzzy MCDM Selection Technique." In 2007 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making. IEEE, 2007. http://dx.doi.org/10.1109/mcdm.2007.369437.
Full textReports on the topic "Multi-criteria Design"
Wiecek, Margaret M., Vijay Singh, and Vincent Blouin. Multi-Scenario Multi-Criteria Optimization in Engineering Design. Fort Belvoir, VA: Defense Technical Information Center, January 2007. http://dx.doi.org/10.21236/ada462600.
Full textEngau, A., and M. M. Wiecek. 2D Decision-Making for Multi-Criteria Design Optimization. Fort Belvoir, VA: Defense Technical Information Center, May 2006. http://dx.doi.org/10.21236/ada462566.
Full textGiller, R. A. Position paper: Live load design criteria for Project W-236A Multi-Function Waste Tank Facility. Office of Scientific and Technical Information (OSTI), June 1995. http://dx.doi.org/10.2172/97001.
Full textWang and Cheng. L52020 Extension of Strain Design Criteria to Buried HAZ Defects. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), January 2004. http://dx.doi.org/10.55274/r0011103.
Full textStephens, Yue, and Bandstra. PR-224-094500-R01 Preliminary Target Reliability Levels for On-shore Liquid Pipelines. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), April 2013. http://dx.doi.org/10.55274/r0010799.
Full textRoye, Thorsten. The Right Level of Automation for Industry 4.0. SAE International, May 2022. http://dx.doi.org/10.4271/epr2022013.
Full textFühr, Martin, Julian Schenten, and Silke Kleihauer. Integrating "Green Chemistry" into the Regulatory Framework of European Chemicals Policy. Sonderforschungsgruppe Institutionenanalyse, July 2019. http://dx.doi.org/10.46850/sofia.9783941627727.
Full textEngel, Bernard, Yael Edan, James Simon, Hanoch Pasternak, and Shimon Edelman. Neural Networks for Quality Sorting of Agricultural Produce. United States Department of Agriculture, July 1996. http://dx.doi.org/10.32747/1996.7613033.bard.
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