Academic literature on the topic 'Multi-objective topology optimization'
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Journal articles on the topic "Multi-objective topology optimization"
Lee, Chen Jian Ken, and Hirohisa Noguchi. "515 Multi-objective topology optimization involving 3D surfaces." Proceedings of The Computational Mechanics Conference 2008.21 (2008): 233–34. http://dx.doi.org/10.1299/jsmecmd.2008.21.233.
Full textKunakote, Tawatchai, and Sujin Bureerat. "Multi-objective topology optimization using evolutionary algorithms." Engineering Optimization 43, no. 5 (May 2011): 541–57. http://dx.doi.org/10.1080/0305215x.2010.502935.
Full textGong, Yunyi, Yoshitsugu Otomo, and Hajime Igarashi. "Multi-objective topology optimization of magnetic couplers for wireless power transfer." International Journal of Applied Electromagnetics and Mechanics 64, no. 1-4 (December 10, 2020): 325–33. http://dx.doi.org/10.3233/jae-209337.
Full textGuo, Weian, Ming Chen, Lei Wang, and Qidi Wu. "Hyper multi-objective evolutionary algorithm for multi-objective optimization problems." Soft Computing 21, no. 20 (May 24, 2016): 5883–91. http://dx.doi.org/10.1007/s00500-016-2163-5.
Full textBian, Xiang, Zong De Fang, Kun Qin, Lifei Lian, and Bao Yu Zhang. "Multi-Objective Topology Optimization for Bevel Gear and Geometrical Reconstruction." Applied Mechanics and Materials 278-280 (January 2013): 139–42. http://dx.doi.org/10.4028/www.scientific.net/amm.278-280.139.
Full textZuliani, João Batista Queiroz, Miri Weiss Cohen, Lucas de Souza Batista, and Frederico Gadelha Guimarães. "Multi-objective Topology Optimization with Ant Colony Optimization and Genetic Algorithms." Computer-Aided Design and Applications 12, no. 6 (April 29, 2015): 674–82. http://dx.doi.org/10.1080/16864360.2015.1033328.
Full textQueiroz Zuliani, João Batista, Miri Weiss Cohen, Frederico Gadelha Guimarães, and Carlos Alberto Severiano Junior. "A multi-objective approach for multi-material topology and shape optimization." Engineering Optimization 51, no. 6 (September 25, 2018): 915–40. http://dx.doi.org/10.1080/0305215x.2018.1514501.
Full textLI, Dongmei. "Multi-objective Topology Optimization of Thermo-mechanical Compliant Mechanisms." Chinese Journal of Mechanical Engineering 24, no. 06 (2011): 1123. http://dx.doi.org/10.3901/cjme.2011.06.1123.
Full textBorovinšek, Matej, Nejc Novak, Matej Vesenjak, Zoran Ren, and Miran Ulbin. "Designing 2D auxetic structures using multi-objective topology optimization." Materials Science and Engineering: A 795 (September 2020): 139914. http://dx.doi.org/10.1016/j.msea.2020.139914.
Full textAguilar Madeira, J. F., H. Rodrigues, and Heitor Pina. "Multi-objective optimization of structures topology by genetic algorithms." Advances in Engineering Software 36, no. 1 (January 2005): 21–28. http://dx.doi.org/10.1016/j.advengsoft.2003.07.001.
Full textDissertations / Theses on the topic "Multi-objective topology optimization"
Haidine, Abdelfatteh. "Multi-objective combinatorial optimization in topology planning of wireline broadband access networks." Köln WiKu-Verl, 2008. http://d-nb.info/99229200X/04.
Full textCurwen, Vincent, and Alexander Saxin. "Analysis and optimal design of a titanium aircraft bracket using topology optimization." Thesis, Högskolan i Skövde, Institutionen för ingenjörsvetenskap, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-20004.
Full textPardo, María Alejandra Guzmán. "Técnicas de otimização baseadas em quimiotaxia de bactérias." Universidade de São Paulo, 2009. http://www.teses.usp.br/teses/disponiveis/18/18146/tde-19012011-120319/.
Full textIn general, chemotaxis is the biased movement developed by certain living organisms as a response to chemical gradients present in their environment. A bacterium is a unicellular organism that uses chemotaxis as a mechanism for mobilization that allows it to find nutrients needed to survive and to escape from harmful environments. Millions of years of natural evolution became bacterial chemotaxis a highly optimized process in searching and exploration of unknown spaces. Thanks to advances in the computing field, bacterial chemotactical strategies and its excellent ability in searching can be modeled, simulated and emulated developing bio-inspired optimization methods as alternatives to classical methods. Two algorithms based on bacterial chemotactical strategies were designed, developed and implemented in this work: i) the topology optimization algorithm, BCBTOA (Bacterial Chemotaxis Based Topology Optimization Algorithm) and ii) the multi-objective optimization algorithm, BCMOA (Bacterial Chemotaxis Multiobjective Optimization Algorithm). Algorithms performances were evaluated by their applications in the solution of benchmark problems and the results obtained were compared with other algorithms also relevant today. The BCMOA developed here was also applied in the solution of three mechanical design problems. The results obtained as well as the comparative analysis conducted lead to conclude that the algorithms developed were competitive. This also demonstrates the potential of bacterial chemotaxis as a process in which distributed optimization techniques can be inspired.
Li, Yilun. "Numerical methodologies for topology optimization of electromagnetic devices." Thesis, Sorbonne université, 2019. http://www.theses.fr/2019SORUS228.
Full textTopology optimization is the conceptual design of a product. Comparing with conventional design approaches, it can create a novel topology, which could not be imagined beforehand, especially for the design of a product without prior-experiences or knowledge. Indeed, the topology optimization technique with the ability of finding efficient topologies starting from scratch has become a serious asset for the designers. Although originated from structure optimization, topology optimization in electromagnetic field has flourished in the past two decades. Nowadays, topology optimization has become the paradigm of the predominant engineering techniques to provide a quantitative design method for modern engineering design. However, due to its inherent complex nature, the development of applicable methods and strategies for topology optimization is still in progress. To address the typical problems and challenges encountered in an engineering optimization process, considering the existing methods in the literature, this thesis focuses on topology optimization methods based on deterministic and stochastic algorithms. The main work and achievement can be summarized as: Firstly, to solve the premature convergence to a local optimal point of existing ON/OFF method, a Tabu-ON/OFF, an improved Quantum-inspired Evolutionary Algorithm (QEA) and an improved Genetic Algorithm (GA) are proposed successively. The characteristics of each algorithm are elaborated, and its performance is compared comprehensively. Secondly, to solve the intermediate density problem encountered in density-based methods and the engineering infeasibility of the finally optimized topology, two topology optimization methods, namely Solid Isotropic Material with Penalization-Radial Basis Function (SIMP-RBF) and Level Set Method-Radial Basis Function (LSM-RBF) are proposed. Both methods calculate the sensitivity information of the objective function, and use deterministic optimizers to guide the optimizing process. For the problem with a large number of design variables, the computational cost of the proposed methods is greatly reduced compared with those of the methods accounting on stochastic algorithms. At the same time, due to the introduction of RBF data interpolation smoothing technique, the optimized topology is more conducive in actual productions. Thirdly, to reduce the excessive computing costs when a stochastic searching algorithm is used in topology optimization, a design variable redistribution strategy is proposed. In the proposed strategy, the whole searching process of a topology optimization is divided into layered structures. The solution of the previous layer is set as the initial topology for the next optimization layer, and only elements adjacent to the boundary are chosen as design variables. Consequently, the number of design variables is reduced to some extent; and the computation time is thereby shortened. Finally, a multi-objective topology optimization methodology based on the hybrid multi-objective optimization algorithm combining Non-dominated Sorting Genetic Algorithm II (NSGAII) and Differential Evolution (DE) algorithm is proposed. The comparison results on test functions indicate that the performance of the proposed hybrid algorithm is better than those of the traditional NSGAII and Strength Pareto Evolutionary Algorithm 2 (SPEA2), which guarantee the good global optimal ability of the proposed methodology, and enables a designer to handle constraint conditions in a direct way. To validate the proposed topology optimization methodologies, two study cases are optimized and analyzed
Akteke-ozturk, Basak. "New Approaches To Desirability Functions By Nonsmooth And Nonlinear Optimization." Phd thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12612649/index.pdf.
Full texts desirability functions being used throughout this thesis are still the most preferred ones in practice and many other versions are derived from these. On the other hand, they have a drawback of containing nondifferentiable points and, hence, being nonsmooth. Current approaches to their optimization, which are based on derivative-free search techniques and modification of the functions by higher-degree polynomials, need to be diversified considering opportunities offered by modern nonlinear (global) optimization techniques and related softwares. A first motivation of this work is to develop a new efficient solution strategy for the maximization of overall desirability functions which comes out to be a nonsmooth composite constrained optimization problem by nonsmooth optimization methods. We observe that individual desirability functions used in practical computations are of mintype, a subclass of continuous selection functions. To reveal the mechanism that gives rise to a variation in the piecewise structure of desirability functions used in practice, we concentrate on a component-wise and generically piecewise min-type functions and, later on, max-type functions. It is our second motivation to analyze the structural and topological properties of desirability functions via piecewise max-type functions. In this thesis, we introduce adjusted desirability functions based on a reformulation of the individual desirability functions by a binary integer variable in order to deal with their piecewise definition. We define a constraint on the binary variable to obtain a continuous optimization problem of a nonlinear objective function including nondifferentiable points with the constraints of bounds for factors and responses. After describing the adjusted desirability functions on two well-known problems from the literature, we implement modified subgradient algorithm (MSG) in GAMS incorporating to CONOPT solver of GAMS software for solving the corresponding optimization problems. Moreover, BARON solver of GAMS is used to solve these optimization problems including adjusted desirability functions. Numerical applications with BARON show that this is a more efficient alternative solution strategy than the current desirability maximization approaches. We apply negative logarithm to the desirability functions and consider the properties of the resulting functions when they include more than one nondifferentiable point. With this approach we reveal the structure of the functions and employ the piecewise max-type functions as generalized desirability functions (GDFs). We introduce a suitable finite partitioning procedure of the individual functions over their compact and connected interval that yield our so-called GDFs. Hence, we construct GDFs with piecewise max-type functions which have efficient structural and topological properties. We present the structural stability, optimality and constraint qualification properties of GDFs using that of max-type functions. As a by-product of our GDF study, we develop a new method called two-stage (bilevel) approach for multi-objective optimization problems, based on a separation of the parameters: in y-space (optimization) and in x-space (representation). This approach is about calculating the factor variables corresponding to the ideal solutions of each individual functions in y, and then finding a set of compromised solutions in x by considering the convex hull of the ideal factors. This is an early attempt of a new multi-objective optimization method. Our first results show that global optimum of the overall problem may not be an element of the set of compromised solution. The overall problem in both x and y is extended to a new refined (disjunctive) generalized semi-infinite problem, herewith analyzing the stability and robustness properties of the objective function. In this course, we introduce the so-called robust optimization of desirability functions for the cases when response models contain uncertainty. Throughout this thesis, we give several modifications and extensions of the optimization problem of overall desirability functions.
Pinho, Flávio Augusto Xavier Carneiro. "Métodos de densidade em otimização de topologia aplicados a subsistemas de edifícios." Universidade Federal de Goiás, 2015. http://repositorio.bc.ufg.br/tede/handle/tede/5187.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES
Optimization techniques have been widely used in different engineering applications. In the case of structural conception, these techniques can be applied from the architectural concept, determining, for example, bracing structures to setting the best topology for concrete structures, as those compared to strut and tie models. In this context, this thesis presents techniques applied to topology optimization in subsystems of buildings. It is also presented a new software tool, modelled in object-oriented programming, seeking the solution for topology optimization problems assembling various technical problems unified in a single approach. The software tool was used to determine the best shape to bracing frames on a building submited to different loading combinations as well to compare the strut and tie models to foundation blocks. Results were compared to literature review, validating the unified computational procedure. Strut and tie models found in literature were compared to piled foundation blocks varying the number of piles, and whose geometry for larger number of piles are still not clearly defined.
Técnicas de otimização têm sido especialmente utilizadas em diversos problemas de engenharia. No caso da concepção estrutural de grandes edifícios, essas técnicas podem ser utilizadas desde o partido arquitetônico. Neste caso, podem ser determinadas, por exemplo, estruturas de contraventamento. Outro exemplo é a aplicação da otimização de topologia para determinação do modelo de bielas e tirantes de estruturas de concreto armado. Neste trabalho, são utilizadas técnicas de otimização de topologia aplicadas em subsistemas de edifícios. Apresenta-se um software em linguagem de programação orientada a objeto para a solução de problemas de otimização de topologia em que são reunidas diferentes técnicas características do problema as quais são unificadas em uma única abordagem. Esse software é aplicado para determinar a melhor forma da estrutura de contraventamento de edifícios altos submetidos a diversas combinações de carregamentos e para determinação do modelo de bielas e tirantes de blocos de fundações. Os resultados encontrados validam a utilização da uma abordagem unificada já que são condizentes com a literatura. Os modelos de bielas e tirantes encontrados para os blocos de fundações são iguais aos modelos clássicos encontrados na literatura. Também foram estudados blocos de fundações com uma maior quantidade de estacas cujos modelos ainda não possuem geometria bem definida na literatura.
Oliveira, Giovana Trindade da Silva. "Projeto ótimo de robôs manipuladores 3r considerando a topologia do espaço de trabalho." Universidade Federal de Uberlândia, 2012. https://repositorio.ufu.br/handle/123456789/14706.
Full textSeveral studies have investigated the properties of the workspace of opened robotic chains (or serial) with the purpose of emphasizing its geometric and kinematic characteristics, to devise analytical algorithms and procedures for its design. The workspace of a robot manipulator is considered of great interest from theoretical and practical viewpoint. In classical applications in industry, manipulators need to pass through singularities in the joint space to change their posture. A 3-DOF manipulator can execute a non-singular change of posture if and only if there is at least one point in its workspace which has exactly three coincident solutions of the Inverse Kinematic Model (IKM). It is very difficult to express this condition directly from the kinematic model. Thus, in this work, the algebraic tool Gröbner basis is used to obtain an equation for splitting the regions with different types of 3R orthogonal manipulators. The determinant of Jacobian matrix of the direct kinematic model is considered equal to zero to obtain the other surfaces of separation. In addition, is presented a classification of 3R orthogonal manipulators related to the number of solutions in IKM, the number of cusp points and nodes. Some problems of multi-objective optimization are proposed to obtain the optimal design of robots. First considering a general case where the aim is to maximize the volume of the workspace, maximize the stiffness of the joint system and optimize the dexterity of the manipulator without the imposition of restrictions. Next, the optimization problem is subject to penalties that control the topology, making it possible to obtain solutions which satisfy the predetermined topologies. Solutions are presented for the case r3 null and r3 not null. The optimization problem is investigated by using a deterministic technique and two evolutionary algorithms. Some numerical applications are presented to show the efficiency of the proposed methodology.
Diversos estudos têm investigado as propriedades do espaço de trabalho de cadeias robóticas abertas com o objetivo de enfatizar suas características geométricas e cinemáticas, criar algoritmos analíticos e procedimentos para o seu projeto. O espaço de trabalho de um robô manipulador é considerado de grande interesse do ponto de vista teórico e prático. Em aplicações clássicas na indústria, manipuladores precisam passar por singularidades no espaço das juntas para mudar sua postura. Um manipulador com três graus de liberdade pode executar uma mudança de postura não singular se, e somente se, existe pelo menos um ponto em seu espaço de trabalho que tem exatamente três soluções coincidentes do Modelo Geométrico Inverso (MGI). É muito difícil expressar esta condição a partir do modelo cinemático. Assim, neste trabalho, a ferramenta algébrica base de Groebner é utilizada para obter uma das equações que separam as regiões que possuem diferentes tipos de manipuladores 3R ortogonais. O determinante da matriz Jacobiana do Modelo Geométrico Direto é considerado nulo para obter as demais superfícies de separação. Além disso, apresenta-se uma classificação dos manipuladores 3R ortogonais em relação ao número de soluções no MGI, o número de pontos de cúspides e o número de nós. Alguns problemas de otimização multi-objetivo são propostos visando obter o projeto ótimo de robôs. Primeiramente, considera-se o caso geral, cujo objetivo é maximizar o volume do espaço de trabalho, maximizar a rigidez do sistema de juntas e otimizar a destreza do manipulador sem a imposição de restrições. Em seguida, o problema de otimização é sujeito a penalidades que controlam a topologia, tornando possível a obtenção de soluções que obedeçam as topologias pré-estabelecidas. São apresentadas as soluções para o caso r3 nulo e para r3 não nulo. O problema de otimização é investigado aplicando uma técnica determinística e dois algoritmos evolutivos. Algumas aplicações numéricas são apresentadas para mostrar a eficiência da metodologia proposta.
Doutor em Engenharia Mecânica
Jiang, Yi-Syuan, and 江倚瑄. "Topology Optimization of a Load Cell via a Multi-objective Genetic Algorithm." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/37469397528422536759.
Full text國立臺灣大學
機械工程學研究所
104
A load cell for measuring the lift force generated by flapping wings of an insect must have a high fundamental frequency and low stiffness to meet the stringent precision requirements. This thesis aims to design a load cell that can record the waveform of the lift of an insect accurately. Starting from a rectangular shape with specified material properties, a multi-objective genetic algorithm, called NSGA-II, is employed to find the optimal shape of the load cell. A finite element analysis program is developed to determine the values of the objective functions. In NSGA-II, the non-dominated sorting method and crowded-comparison approach are used to increase the genetic diversity as well as keep the elite genes. Because the boundary conditions and applied force are symmetric with respect to the central line of the load cell, we restrict the outcomes of the optimization program to symmetrical structures. The restriction is then removed. The performance of the asymmetrical optimal results thus generated is compared with that of the performance of the symmetrical ones. In order to reduce the computation time, the optimization is first performed on a coarse mesh for the generation of primitive structures. Then the meshes of some specified areas of a primitive optimal structure are refined. Optimization is performed on the refined meshes to determine the final topology of the load cell. In this way, the computational burden can be largely reduced. Prototypes of several optimal designs are manufactured by 3D printing. Experimental test results for the fundamental frequency and flexibility of these prototypes are compared with those of the numerical simulation.
Tsai, Chih-Chieh, and 蔡至捷. "Topology Optimization of a Load Cell via a Multi-objective Particle Swarm Algorithm." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/9uup2e.
Full text國立臺灣大學
機械工程學研究所
106
A good load cell should have a wide band-width and large flexibility to meet the demand of high resolution. It’s very difficult to satisfy these two conflicting demands. This research aims to find a proper design, thorough topology optimization, of a load cell possessing both proper band-width and flexibility. The load cell studied in this thesis is a planar frame. The position of every joint and cross-section area of each rod are used as design variables. The objective functions are the fundamental frequency and the static deflection at the free end of the structure. The Pareto solutions in the design space are located by a multi-objective particle swarm optimization (MOPSO) algorithm. The values of the objective functions are determined using an in-house finite element method code. The MOPSO algorithm proposed by Coello [1], which introduces a mutation operator and a roulette-wheel selection scheme for maintaining the diversity of the particles, is employed to find the optimal designs. In this thesis, several schemes for constructing the frame of the load cell are tested. The symmetrical structures with angle braces have the best performance. In order to find proper designs in a feasible time, we first determine the primary frames under the restriction that the every rod has the same cross-sectional area. Then a primary design in the Pareto set is chosen and further optimized. In the final optimization process, the cross-sectional dimensions of each rod as well as the coordinates of each joint are used as design variables. The final optimal designs are compared with previous designs obtained using different topological optimization algorithms.
Kang, Yu-Chia, and 康祐嘉. "An Integrated Method of Moving Asymptotes and Fuzzy Theory for Multi-objective Topology Optimization." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/71101397953729470644.
Full text淡江大學
航空太空工程學系碩士班
100
An integrated method of moving asymptotes and fuzzy theory for multi-objective topology optimization is developed in this study. The finite element analysis software ANSYS is used for structural analysis. By using the method of material distribution with method of moving asymptotes, the optimum topology design of structure is obtained. In this paper, the multi-objective optimization problem transfer to single optimization problem by utilizing the concept of the fuzzy theory, which is using membership function and intersection set of decision-making. After implementing the concept above, the Pareto solution of the multi-objective topology optimization problem can be obtained. Three stages of topology design were employed in this study. In first stage, a dual method is used to obtain the initial topology design. To eliminate unnecessary element and retain necessary element by element growth-removal combined method (EGRCM) in second stage. The B-Spline curve is used to smooth the design shape in the final stage. Four different multi-objective problems are demonstrated in this paper. The topology optimization result will be discussed in each stage. After using three stages topology design, the results shows that the optimum shapes of structures are more clear and smooth.
Book chapters on the topic "Multi-objective topology optimization"
Giusti, Sebastián Miguel, and Antonio André Novotny. "Multi-objective Topology Optimization Design of Micro-structures." In Computational Modeling, Optimization and Manufacturing Simulation of Advanced Engineering Materials, 21–47. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-04265-7_2.
Full textNajafabadi, Hossein R., Tiago G. Goto, Thiago C. Martins, Ahmad Barari, and Marcos S. G. Tsuzuki. "Multi-objective Topology Optimization Using Simulated Annealing Method." In Advances in Intelligent Systems and Computing, 343–53. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-63403-2_31.
Full textMunk, David J., Gareth A. Vio, Grant P. Steven, and Timoleon Kipouros. "Producing Smart Pareto Sets for Multi-objective Topology Optimisation Problems." In Advances in Structural and Multidisciplinary Optimization, 145–62. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67988-4_10.
Full textMunk, David J., Timoleon Kipouros, and Gareth A. Vio. "A Generalized SNC-BESO Method for Multi-objective Topology Optimization." In EngOpt 2018 Proceedings of the 6th International Conference on Engineering Optimization, 3–14. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-97773-7_1.
Full textXu, Jianan, Xin Gao, and Dongyue Qu. "Multi-objective Topology Optimization for Supporting Plate of Winch Drum Spindle." In Advances in Mechanical Design, 389–402. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-6553-8_27.
Full textZăvoianu, Alexandru-Ciprian, Gerd Bramerdorfer, Edwin Lughofer, and Susanne Saminger-Platz. "Multi-objective Topology Optimization of Electrical Machine Designs Using Evolutionary Algorithms with Discrete and Real Encodings." In Computer Aided Systems Theory – EUROCAST 2017, 331–38. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-74718-7_40.
Full textAulig, N., S. Menzel, E. Nutwell, and D. Detwiler. "Towards multi-objective topology optimization of structures subject to crash and static load cases." In Engineering Optimization 2014, 847–52. CRC Press, 2014. http://dx.doi.org/10.1201/b17488-151.
Full textSahini, Deepak Kumar, Joyjeet Ghose, Sanjay Kumar Jha, Ajit Behera, and Animesh Mandal. "Optimization and Simulation of Additive Manufacturing Processes." In Advances in Civil and Industrial Engineering, 187–209. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-4054-1.ch010.
Full textConference papers on the topic "Multi-objective topology optimization"
Olympio, Kingnide, and Farhan Gandhi. "Skin Designs Using Multi-Objective Topology Optimization." In 49th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference
16th AIAA/ASME/AHS Adaptive Structures Conference
10t. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2008. http://dx.doi.org/10.2514/6.2008-1793.
Chu, Xu-yang, Hui-huang Xu, Gui-fang Shao, and Wei-feng Zheng. "Multi-objective topology optimization for industrial robot." In 2016 IEEE International Conference on Information and Automation (ICIA). IEEE, 2016. http://dx.doi.org/10.1109/icinfa.2016.7832132.
Full textStreichert, Thilo, Christian Haubelt, and Jurgen Teich. "Multi-Objective Topology Optimization for Networked Embedded Systems." In 2006 International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation. IEEE, 2006. http://dx.doi.org/10.1109/icsamos.2006.300814.
Full textTurevsky, Inna, and Krishnan Suresh. "Tracing the Envelope of the Objective-Space in Multi-Objective Topology Optimization." In ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2011. http://dx.doi.org/10.1115/detc2011-47329.
Full textHatzakis, Iason, and David Wallace. "Topology of Anticipatory Populations for Evolutionary Dynamic Multi-Objective Optimization." In 11th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2006. http://dx.doi.org/10.2514/6.2006-7071.
Full textNathan, Nathan, Pramudita S. Palar, and Lavi Rizki Zuhal. "A Multi-objective Approach for Robust Structural Topology Optimization." In AIAA Scitech 2021 Forum. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2021. http://dx.doi.org/10.2514/6.2021-1777.
Full textLiang Liang, Jie Zhang, Li-Ping Chen, and Xiao-hong Zhang. "FVM-based multi-objective topology optimization and Matlab implementation." In 2010 International Conference on Computer Application and System Modeling (ICCASM 2010). IEEE, 2010. http://dx.doi.org/10.1109/iccasm.2010.5619042.
Full textJiang, Chuan, HongYi Hu, ZhiZhou Xu, and RuZhen Liu. "The U-type Platform Multi-objective Topology Optimization Research." In 4th International Conference on Computer, Mechatronics, Control and Electronic Engineering. Paris, France: Atlantis Press, 2015. http://dx.doi.org/10.2991/iccmcee-15.2015.242.
Full textPadhye, Nikhil. "Topology optimization of compliant mechanism using multi-objective particle swarm optimization." In the 2008 GECCO conference companion. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1388969.1388983.
Full textZuliani, João Batista, Miri Cohen, Lucas de Souza Batista, and Frederico Gadelha Guimarães. "Multi-objective Topology Optimization with Ant Colony Optimization and Genetic Algorithms." In CAD'14. CAD Solutions LLC, 2014. http://dx.doi.org/10.14733/cadconfp.2014.170-172.
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