Relevant bibliographies by topics / Evolutionary structural optimisation

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Evolutionary structural optimisation'

Author: Grafiati
Published: 4 June 2021
Last updated: 21 February 2023

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Journal articles on the topic "Evolutionary structural optimisation"

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Chen, Yu‐Ming, Kuo‐Shuh Fan, and Ban‐Jwu Shih. "2.5D Nodal based evolutionary structural optimisation." Journal of the Chinese Institute of Engineers 33, no. 6 (2010): 899–908. http://dx.doi.org/10.1080/02533839.2010.9671678.

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Proos, K. A., G. P. Steven, O. M. Querin, and Y. M. Xie. "Stiffness and inertia multicriteria evolutionary structural optimisation." Engineering Computations 18, no. 7 (2001): 1031–54. http://dx.doi.org/10.1108/02644400110404028.

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Querin, O. M., G. P. Steven, and Y. M. Xie. "Evolutionary structural optimisation using an additive algorithm." Finite Elements in Analysis and Design 34, no. 3-4 (2000): 291–308. http://dx.doi.org/10.1016/s0168-874x(99)00044-x.

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Kim, H., M. J. Garcia, O. M. Querin, G. P. Steven, and Y. M. Xie. "Introduction of fixed grid in evolutionary structural optimisation." Engineering Computations 17, no. 4 (2000): 427–39. http://dx.doi.org/10.1108/02644400010334838.

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Querin, O. M., G. P. Steven, and Y. M. Xie. "Evolutionary structural optimisation (ESO) using a bidirectional algorithm." Engineering Computations 15, no. 8 (1998): 1031–48. http://dx.doi.org/10.1108/02644409810244129.

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Guan, Hong, Grant P. Steven, and Yi-Min Xie. "Evolutionary Structural Optimisation Incorporating Tension and Compression Materials." Advances in Structural Engineering 2, no. 4 (1999): 273–88. http://dx.doi.org/10.1177/136943329900200403.

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Chen, G., G. J. Pettet, M. Pearcy, and D. L. S. McElwain. "Modelling external bone adaptation using evolutionary structural optimisation." Biomechanics and Modeling in Mechanobiology 6, no. 4 (2006): 275–85. http://dx.doi.org/10.1007/s10237-006-0055-9.

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Chiu, Louis N. S., Daniel Stojanov, Bernard Rolfe, and Wen Yi Yan. "Effect of Optimisation Parameters in Topology Optimisation." Key Engineering Materials 725 (December 2016): 529–34. http://dx.doi.org/10.4028/www.scientific.net/kem.725.529.

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The Bi-directional Evolutionary Structural Optimisation (BESO) method had been used by many authors for the optimisation of structures. This work sets out to investigate the effect of key optimisation parameters utilized in the BESO method, the evolution rate and the filter radius, on the outcome of the optimisation. An understanding of the interaction of these factors in the optimisation process enables a more efficient way to produce optimised components that can fully capitalise on the capabilities of additive manufacturing.
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Steven, Grant, Osvaldo Querin, and Mike Xie. "Evolutionary structural optimisation (ESO) for combined topology and size optimisation of discrete structures." Computer Methods in Applied Mechanics and Engineering 188, no. 4 (2000): 743–54. http://dx.doi.org/10.1016/s0045-7825(99)00359-x.

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Merten, Errol A. "Application of Evolutionary Structural Optimisation; Reinventing the (Bicycle) Wheel." Applied Mechanics and Materials 553 (May 2014): 830–35. http://dx.doi.org/10.4028/www.scientific.net/amm.553.830.

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This paper reports the application of Evolutionary Structural Optimisation (ESO) to minimise the weight of a bicycle wheel rim. Two finite element models were developed to analyse the rims internal structure. The internal structure of a bicycle wheel rim consists of two walls connected by a rounded spoke bed, and a horizontal spar. One model was constructed with linear plate elements and suggested material should be distributed around the spoke bed and away from the rim walls, however inaccuracies were found in the spar section. ESO of the second model, consisting of linear brick elements pres
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Dissertations / Theses on the topic "Evolutionary structural optimisation"

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Proos, Kaarel. "Evolutionary structural optimisation as a robust and reliable design tool." Connect to full text, 2002. http://hdl.handle.net/2123/519.

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Thesis (Ph. D.)--University of Sydney, 2002.<br>Title from title screen (viewed Apr. 28, 2008). Submitted in fulfilment of the requirements for the degree of Doctor of Philosophy to the School of Aeronautical, Mechatronic and Mechanical Engineering. Includes bibliographical references. Also available in print form.
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Proos, Kaarel Andres. "Evolutionary structural optimisation as a robust and reliable design tool." Thesis, The University of Sydney, 2002. http://hdl.handle.net/2123/519.

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Evolutionary Structural Optimisation (ESO) is a relatively new design tool used to improve and optimise the design of structures. It is a heuristic method where a few elements of an initial design domain of finite elements are iteratively removed. Such a process is carried out repeatedly until an optimum design is achieved, or until a desired given area or volume is reached. There have been many contributions to the ESO procedure since its conception back in 1992. For example, a provision known as Bi-Directional ESO (BESO) has now been incorporated where elements may not only be removed,
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Proos, Kaarel Andres. "Evolutionary structural optimisation as a robust and reliable design tool." University of Sydney. Aerospace, 2002. http://hdl.handle.net/2123/519.

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Evolutionary Structural Optimisation (ESO) is a relatively new design tool used to improve and optimise the design of structures. It is a heuristic method where a few elements of an initial design domain of finite elements are iteratively removed. Such a process is carried out repeatedly until an optimum design is achieved, or until a desired given area or volume is reached. There have been many contributions to the ESO procedure since its conception back in 1992. For example, a provision known as Bi-Directional ESO (BESO) has now been incorporated where elements may not only be removed,
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Wong, Kin Ming. "Evolutionary structural form optimisation for lateral stiffness design of tall buildings /." View abstract or full-text, 2007. http://library.ust.hk/cgi/db/thesis.pl?CIVL%202007%20WONGK.

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Cervera, Eva. "Evolutionary structural optimisation based on boundary element representation of B-spline geometry." Thesis, Durham University, 2003. http://etheses.dur.ac.uk/2004/.

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Evolutionary Structural Optimisation (ESO) has become a well-established technique for determining the optimum shape and topology of a structure given a set of loads and constraints. The basic ESO concept that the optimum topology design evolves by slow removal and addition of material has matured over the last ten years. Nevertheless, the development of the method has almost exclusively considered finite elements (FE) as the approach for providing stress solutions. This thesis presents an ESO approach based on the boundary element method. Non-uniform rational B-splines (NURBS) are used to def
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Kelly, Liam. "Reducing design time : the impact of evolutionary structural optimisation on structural trade studies during preliminary design." Thesis, University of Southampton, 2015. https://eprints.soton.ac.uk/380508/.

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Aircraft design is an inherently multi-disciplinary decision making process. In many design processes, the vehicle configuration is selected based on aerodynamic considerations in the concept design stage, before the structural layout is considered during preliminary design. Selection of the best vehicle configuration relies on an estimate of weight to determine the required lift of the aircraft. Structural topology optimisation is an efficient method for automatically generating a structural design layout that fits within a given design space and meets a given set of design criteria. By compa
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Brodie, Robert Neil. "Development of controllability and robustness methodologies for Bi-directional Evolutionary Structural Optimisation (BESO)." Thesis, University of Leeds, 2007. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.486156.

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Agyei, Eugene Osei. "Groundwater modeling and management using the finite element method and evolutionary optimisation techniques /." Title page, synopsis and contents only, 1997. http://web4.library.adelaide.edu.au/theses/09PH/09pha284.pdf.

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Ebenhöh, Oliver. "Structural analysis of metabolic networks." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät I, 2003. http://dx.doi.org/10.18452/14853.

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In der vorliegenden Arbeit werden zwei Modelle zur strukturellen Analyse von Stoffwechselsystemen vorgestellt. Die Untersuchung basiert auf der Hypothese, dass heutzutage vorzufindende Stoffwechselsysteme als Ergebnis einer evolutionären Entwicklung, bestimmt durch Mutationsmechanismen und natürlicher Selektion, angesehen werden können. Es kann daher angenommen werden, dass kinetische Parameter sowie strukturelle Eigenschaften im Laufe der Evolution solche Werte angenommen haben, die eine gewisse Optimalität bezüglich ihrer biologischen Funktion darstellen. Das erste Modell untersucht das str
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Damp, Lloyd Hollis. "Multi-Objective and Multidisciplinary Design Optimisation of Unmanned Aerial Vehicle Systems using Hierarchical Asynchronous Parallel Multi-Objective Evolutionary Algorithms." Thesis, The University of Sydney, 2007. http://hdl.handle.net/2123/1858.

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The overall objective of this research was to realise the practical application of Hierarchical Asynchronous Parallel Evolutionary Algorithms for Multi-objective and Multidisciplinary Design Optimisation (MDO) of UAV Systems using high fidelity analysis tools. The research looked at the assumed aerodynamics and structures of two production UAV wings and attempted to optimise these wings in isolation to the rest of the vehicle. The project was sponsored by the Asian Office of the Air Force Office of Scientific Research under contract number AOARD-044078. The two vehicles wings which were optim
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Books on the topic "Evolutionary structural optimisation"

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Genetic algorithms + data structures = evolution programs. 2nd ed. Springer-Verlag, 1994.

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Genetic algorithms + data structures = evolution programs. Springer-Verlag, 1992.

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Genetic algorithms + data structures = evolution programs. 3rd ed. Springer-Verlag, 1996.

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Michalewicz, Zbigniew. Genetic Algorithms + Data Structures =: Evolution Programs. Springer Berlin Heidelberg, 1994.

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Michalewicz, Zbigniew. Algorytmy genetyczne + struktury danych = programy ewolucyjne. 3rd ed. Wydawnictwa Naukowo-Techniczne, 2003.

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Allaire, Grégoire. Conception optimale de structures (Mathématiques et Applications). Springer, 2006.

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Michalewicz, Zbigniew. Genetic Algorithms + Data Structures = Evolution Programs. Springer, 2014.

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Michalewicz, Zbigniew. Genetic Algorithms + Data Structures = Evolution Programs. Springer London, Limited, 2013.

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Michalewicz, Zbigniew. Genetic Algorithms + Data Structures = Evolution Programs. Springer London, Limited, 2013.

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Michalewicz, Zbigniew. Genetic Algorithms + Data Structures = Evolution Programs. Springer, 2011.

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Book chapters on the topic "Evolutionary structural optimisation"

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Querin, O. M., G. P. Steven, and Y. M. Xie. "Advances in Evolutionary Structural Optimisation: 1992-2000." In Topology Optimization of Structures and Composite Continua. Springer Netherlands, 2000. http://dx.doi.org/10.1007/978-94-010-0910-2_16.

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Kim, H., O. M. Querin, and G. P. Steven. "Post-Processing of the Two-Dimensional Evolutionary Structural Optimisation Topologies." In Evolutionary Design and Manufacture. Springer London, 2000. http://dx.doi.org/10.1007/978-1-4471-0519-0_3.

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González, L. F., L. Damp, J. Périaux, and K. Srinivas. "High-Fidelity Multi-criteria Aero-structural Optimisation using Hierarchical Parallel Evolutionary Algorithms." In Computational Fluid Dynamics 2006. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-92779-2_85.

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S. P. da Costa, Mariana, Joss Kesby, and Philip D. Clausen. "Structural Optimisation of 3D Printed Small Diffuser Augmented Wind Turbine Blade Using Bi-directional Evolutionary Layout Optimisation Method." In Wind Energy Exploitation in Urban Environment. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-13531-7_13.

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Feng, Z., P. Gu, M. Zheng, X. Yan, and D. W. Bao. "Environmental Data-Driven Performance-Based Topological Optimisation for Morphology Evolution of Artificial Taihu Stone." In Proceedings of the 2021 DigitalFUTURES. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-5983-6_11.

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AbstractTaihu stone is the most famous one among the top four stones in China. It is formed by the water's erosion in Taihu Lake for hundreds or even thousands of years. It has become a common ornamental stone in classical Chinese gardens because of its porous and intricate forms. At the same time, it has become a cultural symbol through thousands of years of history in China; later, people researched its spatial aesthetics; there are also some studies on its structural properties. For example, it has been found that the opening of Taihu stone caves has a steady-state effect which people develop its value in the theory of Poros City, Porosity in Architecture and some cultural symbols based on the original ornamental value of Taihu stone. This paper introduces a hybrid generative design method that integrates the Computational Fluid Dynamics (CFD) and Bi-directional Evolutionary Structural Optimization (BESO) techniques. Computational Fluid Dynamics (CFD) simulation enables architects and engineers to predict and optimise the performance of buildings and environment in the early stage of the design and topology optimisation techniques BESO has been widely used in structural design to evolve a structure from the full design domain towards an optimum by gradually removing inefficient material and adding materials simultaneously. This research aims to design the artificial Taihu stone based on the environmental data-driven performance feedback using the topological optimisation method. As traditional and historical ornament craftwork in China, the new artificial Taihu stone stimulates thinking about the new value and unique significance of the cultural symbol of Taihu stone in modern society. It proposes possibilities and reflections on exploring the related fields of Porosity in Architecture and Poros City from the perspective of structure.
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Hofmann, Arne. "We look for evolutionary optimisation of structures." In What is the Architect Doing in the Jungle? Biornametics. Springer Vienna, 2013. http://dx.doi.org/10.1007/978-3-7091-1529-9_7.

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Lane, Peter, Na Helian, Muhammad Haad Bodla, Minghua Zheng, and Paul Moggridge. "Dynamic Hierarchical Structure Optimisation for Cloud Computing Job Scheduling." In Applications of Evolutionary Computation. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-02462-7_20.

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Kulikov, Gennady G., and Haydn A. Thompson. "Nonlinear Model Structure Selection Using Evolutionary Optimisation Methods." In Advances in Industrial Control. Springer London, 2004. http://dx.doi.org/10.1007/978-1-4471-3796-2_9.

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Brownlee, Alexander E. I., John A. W. McCall, Siddhartha K. Shakya, and Qingfu Zhang. "Structure Learning and Optimisation in a Markov Network Based Estimation of Distribution Algorithm." In Evolutionary Learning and Optimization. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12834-9_3.

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Hämmerle-Uhl, Jutta, Michael Karnutsch, and Andreas Uhl. "Evolutionary Optimisation of JPEG2000 Part 2 Wavelet Packet Structures for Polar Iris Image Compression." In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-41822-8_49.

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Conference papers on the topic "Evolutionary structural optimisation"

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Weis, Lennart, Hardy Koke, and Christian Huhne. "Structural optimisation of a composite aircraft frame applying a particle swarm algorithm." In 2015 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2015. http://dx.doi.org/10.1109/cec.2015.7256943.

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Vio, Gareth, and Jonathan Cooper. "Optimisation of Composite Structures for Aeroelastic Applications Using Evolutionary Algorithms." In 49th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference
16th AIAA/ASME/AHS Adaptive Structures Conference
10t. American Institute of Aeronautics and Astronautics, 2008. http://dx.doi.org/10.2514/6.2008-1972.

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van Wyk, David, and David Jonson. "The Design of Advanced Composite Structures Using Evolutionary Design Methods." In ASME 8th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2006. http://dx.doi.org/10.1115/esda2006-95775.

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The development of an evolutionary optimisation method and its application to the design of an advanced composite structure is discussed. Composite materials are increasingly being used in various fields, and so optimisation of such structures would be advantageous. From among the various methods available, one particular method, known as Evolutionary Structural Optimisation (ESO), is shown here. ESO is an empirical method, based on the concept of removing and adding material from a structure, in order to create an optimum shape. Much work has been done on ESO by various researchers. V. Young,
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Gentile, Lorenzo, Cristian Greco, Edmondo Minisci, Thomas Bartz-Beielstein, and Massimiliano Vasile. "Structured-chromosome GA optimisation for satellite tracking." In GECCO '19: Genetic and Evolutionary Computation Conference. ACM, 2019. http://dx.doi.org/10.1145/3319619.3326841.

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Kononova, Anna V., Fabio Caraffini, Hao Wang, and Thomas Back. "Can Single Solution Optimisation Methods Be Structurally Biased?" In 2020 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2020. http://dx.doi.org/10.1109/cec48606.2020.9185494.

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Vié, Aymeric. "Population network structure impacts genetic algorithm optimisation performance." In GECCO '21: Genetic and Evolutionary Computation Conference. ACM, 2021. http://dx.doi.org/10.1145/3449726.3463134.

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Gentile, Lorenzo, Elisa Morales, Domenico Quagliarella, Edmondo Minisci, Thomas Bartz-Beielstein, and Renato Tognaccini. "High-Lift Devices Topology Optimisation using Structured-Chromosome Genetic Algorithm." In 2020 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2020. http://dx.doi.org/10.1109/cec48606.2020.9185603.

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Herbert, Luke T., and Robin Sharp. "Optimisation of BPMN Business Models via Model Checking." 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/detc2013-13047.

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We present a framework for the optimisation of business processes modelled in the business process modelling language BPMN, which builds upon earlier work, where we developed a model checking based method for the analysis of BPMN models. We define a structure for expressing optimisation goals for synthesized BPMN components, based on probabilistic computation tree logic and real-valued reward structures of the BPMN model, allowing for the specification of complex quantitative goals. We here present a simple algorithm, inspired by concepts from evolutionary algorithms, which iteratively generat
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Greco, Cristian, Lorenzo Gentile, Gianluca Filippi, Edmondo Minisci, Massimiliano Vasile, and Thomas Bartz-Beielstein. "Autonomous Generation of Observation Schedules for Tracking Satellites with Structured-Chromosome GA Optimisation." In 2019 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2019. http://dx.doi.org/10.1109/cec.2019.8790101.

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Brownlee, Alexander E. I., John A. W. McCall, Siddartha K. Shakya, and Qingfu Zhang. "Structure learning and optimisation in a Markov-network based estimation of distribution algorithm." In 2009 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2009. http://dx.doi.org/10.1109/cec.2009.4982980.

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