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In <i>Proceedings of the Foundations of Software Engineering (FSE) and NITR &#38; D/SPD Working Conference on the Future of Software Engineering Research (FoSER)</i> (pp. 321–324).","ieee":"W. Schäfer <i>et al.</i>, “Engineering Self-Coordinating Software Intensive Systems,” in <i>Proceedings of the Foundations of Software Engineering (FSE) and NITR &#38; D/SPD Working Conference on the Future of Software Engineering Research (FoSER)</i>, 2010, pp. 321–324.","chicago":"Schäfer, Wilhelm, Mauro Birattari, Johannes Blömer, Marco Dorigo, Gregor Engels, Rehan O’Grady, Marco Platzner, Franz-Josef Rammig, Wolfgang  Reif, and Ansgar Trächtler. “Engineering Self-Coordinating Software Intensive Systems.” In <i>Proceedings of the Foundations of Software Engineering (FSE) and NITR &#38; D/SPD Working Conference on the Future of Software Engineering Research (FoSER)</i>, 321–24, 2010.","short":"W. Schäfer, M. Birattari, J. Blömer, M. Dorigo, G. Engels, R. O’Grady, M. Platzner, F.-J. Rammig, W. Reif, A. Trächtler, in: Proceedings of the Foundations of Software Engineering (FSE) and NITR &#38; D/SPD Working Conference on the Future of Software Engineering Research (FoSER), 2010, pp. 321–324."},"type":"conference","department":[{"_id":"78"}],"date_created":"2019-10-04T22:35:54Z"},{"publisher":"CSREA Press","_id":"13642","language":[{"iso":"eng"}],"user_id":"398","title":"A Self-Reconfigurable Lightweight Interconnect for Scalable Processor Fabrics","year":"2010","status":"public","author":[{"last_name":"Giefers","first_name":"Heiner","full_name":"Giefers, Heiner"},{"id":"398","last_name":"Platzner","first_name":"Marco","full_name":"Platzner, Marco"}],"date_updated":"2022-01-06T06:51:40Z","date_created":"2019-10-04T22:37:54Z","type":"conference","department":[{"_id":"78"}],"publication":"Proceedings of the 10th International Conference on Engineering of Reconfigurable Systems and Algorithms (ERSA)","citation":{"mla":"Giefers, Heiner, and Marco Platzner. “A Self-Reconfigurable Lightweight Interconnect for Scalable Processor Fabrics.” <i>Proceedings of the 10th International Conference on Engineering of Reconfigurable Systems and Algorithms (ERSA)</i>, CSREA Press, 2010.","bibtex":"@inproceedings{Giefers_Platzner_2010, title={A Self-Reconfigurable Lightweight Interconnect for Scalable Processor Fabrics}, booktitle={Proceedings of the 10th International Conference on Engineering of Reconfigurable Systems and Algorithms (ERSA)}, publisher={CSREA Press}, author={Giefers, Heiner and Platzner, Marco}, year={2010} }","ama":"Giefers H, Platzner M. A Self-Reconfigurable Lightweight Interconnect for Scalable Processor Fabrics. In: <i>Proceedings of the 10th International Conference on Engineering of Reconfigurable Systems and Algorithms (ERSA)</i>. CSREA Press; 2010.","ieee":"H. Giefers and M. Platzner, “A Self-Reconfigurable Lightweight Interconnect for Scalable Processor Fabrics,” in <i>Proceedings of the 10th International Conference on Engineering of Reconfigurable Systems and Algorithms (ERSA)</i>, 2010.","apa":"Giefers, H., &#38; Platzner, M. (2010). A Self-Reconfigurable Lightweight Interconnect for Scalable Processor Fabrics. In <i>Proceedings of the 10th International Conference on Engineering of Reconfigurable Systems and Algorithms (ERSA)</i>. CSREA Press.","short":"H. Giefers, M. Platzner, in: Proceedings of the 10th International Conference on Engineering of Reconfigurable Systems and Algorithms (ERSA), CSREA Press, 2010.","chicago":"Giefers, Heiner, and Marco Platzner. “A Self-Reconfigurable Lightweight Interconnect for Scalable Processor Fabrics.” In <i>Proceedings of the 10th International Conference on Engineering of Reconfigurable Systems and Algorithms (ERSA)</i>. CSREA Press, 2010."}},{"file_date_updated":"2023-10-05T16:55:11Z","citation":{"mla":"Postler, Tim. <i>Smart Card basierte Berechnung einer Gruppensignatur als Teil einer biometrischen Authentisierung</i>. 2010.","ama":"Postler T. <i>Smart Card basierte Berechnung einer Gruppensignatur als Teil einer biometrischen Authentisierung</i>.; 2010.","bibtex":"@book{Postler_2010, title={Smart Card basierte Berechnung einer Gruppensignatur als Teil einer biometrischen Authentisierung}, author={Postler, Tim}, year={2010} }","apa":"Postler, T. (2010). <i>Smart Card basierte Berechnung einer Gruppensignatur als Teil einer biometrischen Authentisierung</i>.","ieee":"T. Postler, <i>Smart Card basierte Berechnung einer Gruppensignatur als Teil einer biometrischen Authentisierung</i>. 2010.","chicago":"Postler, Tim. <i>Smart Card basierte Berechnung einer Gruppensignatur als Teil einer biometrischen Authentisierung</i>, 2010.","short":"T. Postler, Smart Card basierte Berechnung einer Gruppensignatur als Teil einer biometrischen Authentisierung, 2010."},"file":[{"date_updated":"2023-10-05T16:55:11Z","relation":"main_file","file_size":1192529,"access_level":"open_access","file_name":"2010_Postler_SmartCardBasierteBerechnungEinerGruppensignatur.pdf","content_type":"application/pdf","file_id":"47706","creator":"bhenrik","date_created":"2023-10-05T16:21:25Z"}],"date_created":"2023-10-05T16:23:48Z","type":"misc","keyword":["Diplomarbeit"],"department":[{"_id":"34"},{"_id":"64"}],"oa":"1","title":"Smart Card basierte Berechnung einer Gruppensignatur als Teil einer biometrischen Authentisierung","status":"public","year":"2010","author":[{"full_name":"Postler, Tim","last_name":"Postler","first_name":"Tim"}],"date_updated":"2023-10-05T16:55:11Z","has_accepted_license":"1","language":[{"iso":"ger"}],"_id":"47684","user_id":"41047","ddc":["000"]},{"abstract":[{"lang":"eng","text":"The integration of experts’ preferences is an important aspect in multi-objective optimization. Usually, one out of a set of Pareto optimal solutions has to be chosen based on expert knowledge. A combination of multi-objective particle swarm optimization (MOPSO) with the desirability concept is introduced to efficiently focus on desired and relevant regions of the true Pareto front of the optimization problem which facilitates the solution selection process. Desirability functions of the objectives are optimized, and the desirability index is used for selecting the global best particle in each iteration. The resulting MOPSO variant DF-MOPSO in most cases exclusively generates solutions in the desired area of the Pareto front. Approximations of the whole Pareto front result in cases of misspecified desired regions."}],"publication":"Parallel Problem Solving from Nature, PPSN XI","citation":{"ama":"Mostaghim S, Trautmann H, Mersmann O. Preference-Based Multi-Objective Particle Swarm Optimization Using Desirabilities. In: Schaefer R, Cotta C, Kołodziej J, Rudolph G, eds. <i>Parallel Problem Solving from Nature, PPSN XI</i>. Springer Berlin Heidelberg; 2010:101–110. doi:<a href=\"https://doi.org/10.1007/978-3-642-15871-1_11\">https://doi.org/10.1007/978-3-642-15871-1_11</a>","bibtex":"@inproceedings{Mostaghim_Trautmann_Mersmann_2010, place={Berlin, Heidelberg}, title={Preference-Based Multi-Objective Particle Swarm Optimization Using Desirabilities}, DOI={<a href=\"https://doi.org/10.1007/978-3-642-15871-1_11\">https://doi.org/10.1007/978-3-642-15871-1_11</a>}, booktitle={Parallel Problem Solving from Nature, PPSN XI}, publisher={Springer Berlin Heidelberg}, author={Mostaghim, Sanaz and Trautmann, Heike and Mersmann, Olaf}, editor={Schaefer, Robert and Cotta, Carlos and Kołodziej, Joanna and Rudolph, Günter}, year={2010}, pages={101–110} }","mla":"Mostaghim, Sanaz, et al. “Preference-Based Multi-Objective Particle Swarm Optimization Using Desirabilities.” <i>Parallel Problem Solving from Nature, PPSN XI</i>, edited by Robert Schaefer et al., Springer Berlin Heidelberg, 2010, pp. 101–110, doi:<a href=\"https://doi.org/10.1007/978-3-642-15871-1_11\">https://doi.org/10.1007/978-3-642-15871-1_11</a>.","chicago":"Mostaghim, Sanaz, Heike Trautmann, and Olaf Mersmann. “Preference-Based Multi-Objective Particle Swarm Optimization Using Desirabilities.” In <i>Parallel Problem Solving from Nature, PPSN XI</i>, edited by Robert Schaefer, Carlos Cotta, Joanna Kołodziej, and Günter Rudolph, 101–110. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. <a href=\"https://doi.org/10.1007/978-3-642-15871-1_11\">https://doi.org/10.1007/978-3-642-15871-1_11</a>.","short":"S. Mostaghim, H. Trautmann, O. Mersmann, in: R. Schaefer, C. Cotta, J. Kołodziej, G. Rudolph (Eds.), Parallel Problem Solving from Nature, PPSN XI, Springer Berlin Heidelberg, Berlin, Heidelberg, 2010, pp. 101–110.","apa":"Mostaghim, S., Trautmann, H., &#38; Mersmann, O. (2010). Preference-Based Multi-Objective Particle Swarm Optimization Using Desirabilities. In R. Schaefer, C. Cotta, J. Kołodziej, &#38; G. Rudolph (Eds.), <i>Parallel Problem Solving from Nature, PPSN XI</i> (pp. 101–110). Springer Berlin Heidelberg. <a href=\"https://doi.org/10.1007/978-3-642-15871-1_11\">https://doi.org/10.1007/978-3-642-15871-1_11</a>","ieee":"S. Mostaghim, H. Trautmann, and O. Mersmann, “Preference-Based Multi-Objective Particle Swarm Optimization Using Desirabilities,” in <i>Parallel Problem Solving from Nature, PPSN XI</i>, 2010, pp. 101–110, doi: <a href=\"https://doi.org/10.1007/978-3-642-15871-1_11\">https://doi.org/10.1007/978-3-642-15871-1_11</a>."},"type":"conference","department":[{"_id":"34"},{"_id":"819"}],"place":"Berlin, Heidelberg","date_created":"2023-08-04T16:06:43Z","date_updated":"2023-10-16T13:56:31Z","title":"Preference-Based Multi-Objective Particle Swarm Optimization Using Desirabilities","status":"public","year":"2010","publication_identifier":{"isbn":["978-3-642-15871-1"]},"author":[{"full_name":"Mostaghim, Sanaz","first_name":"Sanaz","last_name":"Mostaghim"},{"id":"100740","first_name":"Heike","orcid":"0000-0002-9788-8282","last_name":"Trautmann","full_name":"Trautmann, Heike"},{"full_name":"Mersmann, Olaf","last_name":"Mersmann","first_name":"Olaf"}],"doi":"https://doi.org/10.1007/978-3-642-15871-1_11","user_id":"15504","editor":[{"first_name":"Robert","last_name":"Schaefer","full_name":"Schaefer, Robert"},{"full_name":"Cotta, Carlos","first_name":"Carlos","last_name":"Cotta"},{"first_name":"Joanna","last_name":"Kołodziej","full_name":"Kołodziej, Joanna"},{"full_name":"Rudolph, Günter","first_name":"Günter","last_name":"Rudolph"}],"page":"101–110","_id":"46408","language":[{"iso":"eng"}],"publisher":"Springer Berlin Heidelberg"},{"date_updated":"2023-10-16T13:55:43Z","publication_identifier":{"isbn":["3642158439"]},"author":[{"full_name":"Mersmann, Olaf","last_name":"Mersmann","first_name":"Olaf"},{"last_name":"Preuss","first_name":"Mike","full_name":"Preuss, Mike"},{"id":"100740","last_name":"Trautmann","orcid":"0000-0002-9788-8282","first_name":"Heike","full_name":"Trautmann, Heike"}],"title":"Benchmarking Evolutionary Algorithms: Towards Exploratory Landscape Analysis","status":"public","year":"2010","user_id":"15504","_id":"46405","publisher":"Springer-Verlag","series_title":"PPSN’10","language":[{"iso":"eng"}],"page":"73–82","abstract":[{"text":"We present methods to answer two basic questions that arise when benchmarking optimization algorithms. The first one is: which algorithm is the ’best’ one? and the second one: which algorithm should I use for my real world problem? Both are connected and neither is easy to answer. We present methods which can be used to analyse the raw data of a benchmark experiment and derive some insight regarding the answers to these questions. We employ the presented methods to analyse the BBOB’09 benchmark results and present some initial findings.","lang":"eng"}],"citation":{"mla":"Mersmann, Olaf, et al. “Benchmarking Evolutionary Algorithms: Towards Exploratory Landscape Analysis.” <i>Proceedings of the 11th International Conference on Parallel Problem Solving from Nature: Part I</i>, Springer-Verlag, 2010, pp. 73–82.","bibtex":"@inproceedings{Mersmann_Preuss_Trautmann_2010, place={Berlin, Heidelberg}, series={PPSN’10}, title={Benchmarking Evolutionary Algorithms: Towards Exploratory Landscape Analysis}, booktitle={Proceedings of the 11th International Conference on Parallel Problem Solving from Nature: Part I}, publisher={Springer-Verlag}, author={Mersmann, Olaf and Preuss, Mike and Trautmann, Heike}, year={2010}, pages={73–82}, collection={PPSN’10} }","ama":"Mersmann O, Preuss M, Trautmann H. Benchmarking Evolutionary Algorithms: Towards Exploratory Landscape Analysis. In: <i>Proceedings of the 11th International Conference on Parallel Problem Solving from Nature: Part I</i>. PPSN’10. Springer-Verlag; 2010:73–82.","ieee":"O. Mersmann, M. Preuss, and H. Trautmann, “Benchmarking Evolutionary Algorithms: Towards Exploratory Landscape Analysis,” in <i>Proceedings of the 11th International Conference on Parallel Problem Solving from Nature: Part I</i>, 2010, pp. 73–82.","apa":"Mersmann, O., Preuss, M., &#38; Trautmann, H. (2010). Benchmarking Evolutionary Algorithms: Towards Exploratory Landscape Analysis. <i>Proceedings of the 11th International Conference on Parallel Problem Solving from Nature: Part I</i>, 73–82.","short":"O. Mersmann, M. Preuss, H. Trautmann, in: Proceedings of the 11th International Conference on Parallel Problem Solving from Nature: Part I, Springer-Verlag, Berlin, Heidelberg, 2010, pp. 73–82.","chicago":"Mersmann, Olaf, Mike Preuss, and Heike Trautmann. “Benchmarking Evolutionary Algorithms: Towards Exploratory Landscape Analysis.” In <i>Proceedings of the 11th International Conference on Parallel Problem Solving from Nature: Part I</i>, 73–82. PPSN’10. Berlin, Heidelberg: Springer-Verlag, 2010."},"publication":"Proceedings of the 11th International Conference on Parallel Problem Solving from Nature: Part I","department":[{"_id":"34"},{"_id":"819"}],"keyword":["benchmarking","multidimensional scaling","consensus ranking","evolutionary optimization","BBOB test set"],"type":"conference","date_created":"2023-08-04T16:02:28Z","place":"Berlin, Heidelberg"},{"status":"public","editor":[{"last_name":"Blum","first_name":"C","full_name":"Blum, C"},{"full_name":"Battiti, R","first_name":"R","last_name":"Battiti"}],"volume":6073,"user_id":"15504","publisher":"Springer","_id":"46406","page":"333–337","citation":{"chicago":"Mersmann, O, Heike Trautmann, B Naujoks, and C Weihs. “On the Distribution of EMOA Hypervolumes.” In <i>Learning and Intelligent Optimization, 4$^th$ International Conference, LION 4, Venice, Italy</i>, edited by C Blum and R Battiti, 6073:333–337. Lecture Notes in Computer Science. Springer, 2010.","ama":"Mersmann O, Trautmann H, Naujoks B, Weihs C. On the Distribution of EMOA Hypervolumes. In: Blum C, Battiti R, eds. <i>Learning and Intelligent Optimization, 4$^th$ International Conference, LION 4, Venice, Italy</i>. Vol 6073. Lecture Notes in Computer Science. Springer; 2010:333–337.","short":"O. Mersmann, H. Trautmann, B. Naujoks, C. Weihs, in: C. Blum, R. Battiti (Eds.), Learning and Intelligent Optimization, 4$^th$ International Conference, LION 4, Venice, Italy, Springer, 2010, pp. 333–337.","bibtex":"@inproceedings{Mersmann_Trautmann_Naujoks_Weihs_2010, series={Lecture Notes in Computer Science}, title={On the Distribution of EMOA Hypervolumes}, volume={6073}, booktitle={Learning and Intelligent Optimization, 4$^th$ International Conference, LION 4, Venice, Italy}, publisher={Springer}, author={Mersmann, O and Trautmann, Heike and Naujoks, B and Weihs, C}, editor={Blum, C and Battiti, R}, year={2010}, pages={333–337}, collection={Lecture Notes in Computer Science} }","mla":"Mersmann, O., et al. “On the Distribution of EMOA Hypervolumes.” <i>Learning and Intelligent Optimization, 4$^th$ International Conference, LION 4, Venice, Italy</i>, edited by C Blum and R Battiti, vol. 6073, Springer, 2010, pp. 333–337.","apa":"Mersmann, O., Trautmann, H., Naujoks, B., &#38; Weihs, C. (2010). On the Distribution of EMOA Hypervolumes. In C. Blum &#38; R. Battiti (Eds.), <i>Learning and Intelligent Optimization, 4$^th$ International Conference, LION 4, Venice, Italy</i> (Vol. 6073, pp. 333–337). Springer.","ieee":"O. Mersmann, H. Trautmann, B. Naujoks, and C. Weihs, “On the Distribution of EMOA Hypervolumes,” in <i>Learning and Intelligent Optimization, 4$^th$ International Conference, LION 4, Venice, Italy</i>, 2010, vol. 6073, pp. 333–337."},"intvolume":"      6073","date_updated":"2023-10-16T13:55:59Z","author":[{"full_name":"Mersmann, O","last_name":"Mersmann","first_name":"O"},{"orcid":"0000-0002-9788-8282","last_name":"Trautmann","first_name":"Heike","full_name":"Trautmann, Heike","id":"100740"},{"full_name":"Naujoks, B","last_name":"Naujoks","first_name":"B"},{"full_name":"Weihs, C","last_name":"Weihs","first_name":"C"}],"year":"2010","title":"On the Distribution of EMOA Hypervolumes","series_title":"Lecture Notes in Computer Science","language":[{"iso":"eng"}],"abstract":[{"text":"We present methods to answer two basic questions that arise when benchmarking optimization algorithms. The first one is: which algorithm is the 'best' one? and the second one: which algorithm should I use for my real world problem? Both are connected and neither is easy to answer. We present methods which can be used to analyse the raw data of a benchmark experiment and derive some insight regarding the answers to these questions. We employ the presented methods to analyse the BBOB'09 benchmark results and present some initial findings.","lang":"eng"}],"publication":"Learning and Intelligent Optimization, 4$^th$ International Conference, LION 4, Venice, Italy","department":[{"_id":"34"},{"_id":"819"}],"type":"conference","date_created":"2023-08-04T16:03:45Z"},{"department":[{"_id":"34"},{"_id":"819"}],"type":"conference","date_created":"2023-08-04T16:05:53Z","abstract":[{"lang":"eng","text":"Choosing and tuning an optimization procedure for a given class of nonlinear optimization problems is not an easy task. One way to proceed is to consider this as a tournament, where each procedure will compete in different ‘disciplines’. Here, disciplines could either be different functions, which we want to optimize, or specific performance measures of the optimization procedure. We would then be interested in the algorithm that performs best in a majority of cases or whose average performance is maximal. We will focus on evolutionary multiobjective optimization algorithms (EMOA), and will present a novel approach to the design and analysis of evolutionary multiobjective benchmark experiments based on similar work from the context of machine learning. We focus on deriving a consensus among several benchmarks over different test problems and illustrate the methodology by reanalyzing the results of the CEC 2007 EMOA competition."}],"citation":{"mla":"Mersmann, Olaf, et al. “Benchmarking Evolutionary Multiobjective Optimization Algorithms.” <i>IEEE Congress on Evolutionary Computation</i>, 2010, pp. 1–8, doi:<a href=\"https://doi.org/10.1109/CEC.2010.5586241\">10.1109/CEC.2010.5586241</a>.","bibtex":"@inproceedings{Mersmann_Trautmann_Naujoks_Weihs_2010, title={Benchmarking evolutionary multiobjective optimization algorithms}, DOI={<a href=\"https://doi.org/10.1109/CEC.2010.5586241\">10.1109/CEC.2010.5586241</a>}, booktitle={IEEE Congress on Evolutionary Computation}, author={Mersmann, Olaf and Trautmann, Heike and Naujoks, Boris and Weihs, Claus}, year={2010}, pages={1–8} }","ama":"Mersmann O, Trautmann H, Naujoks B, Weihs C. Benchmarking evolutionary multiobjective optimization algorithms. In: <i>IEEE Congress on Evolutionary Computation</i>. ; 2010:1-8. doi:<a href=\"https://doi.org/10.1109/CEC.2010.5586241\">10.1109/CEC.2010.5586241</a>","ieee":"O. Mersmann, H. Trautmann, B. Naujoks, and C. Weihs, “Benchmarking evolutionary multiobjective optimization algorithms,” in <i>IEEE Congress on Evolutionary Computation</i>, 2010, pp. 1–8, doi: <a href=\"https://doi.org/10.1109/CEC.2010.5586241\">10.1109/CEC.2010.5586241</a>.","apa":"Mersmann, O., Trautmann, H., Naujoks, B., &#38; Weihs, C. (2010). Benchmarking evolutionary multiobjective optimization algorithms. <i>IEEE Congress on Evolutionary Computation</i>, 1–8. <a href=\"https://doi.org/10.1109/CEC.2010.5586241\">https://doi.org/10.1109/CEC.2010.5586241</a>","chicago":"Mersmann, Olaf, Heike Trautmann, Boris Naujoks, and Claus Weihs. “Benchmarking Evolutionary Multiobjective Optimization Algorithms.” In <i>IEEE Congress on Evolutionary Computation</i>, 1–8, 2010. <a href=\"https://doi.org/10.1109/CEC.2010.5586241\">https://doi.org/10.1109/CEC.2010.5586241</a>.","short":"O. Mersmann, H. Trautmann, B. Naujoks, C. Weihs, in: IEEE Congress on Evolutionary Computation, 2010, pp. 1–8."},"publication":"IEEE Congress on Evolutionary Computation","doi":"10.1109/CEC.2010.5586241","user_id":"15504","_id":"46407","language":[{"iso":"eng"}],"page":"1-8","date_updated":"2023-10-16T13:56:15Z","author":[{"first_name":"Olaf","last_name":"Mersmann","full_name":"Mersmann, Olaf"},{"full_name":"Trautmann, Heike","last_name":"Trautmann","first_name":"Heike","orcid":"0000-0002-9788-8282","id":"100740"},{"first_name":"Boris","last_name":"Naujoks","full_name":"Naujoks, Boris"},{"full_name":"Weihs, Claus","first_name":"Claus","last_name":"Weihs"}],"publication_identifier":{"issn":["1941-0026"]},"status":"public","year":"2010","title":"Benchmarking evolutionary multiobjective optimization algorithms"},{"author":[{"first_name":"J","last_name":"Ding","full_name":"Ding, J"},{"full_name":"Wessing, S","first_name":"S","last_name":"Wessing"},{"first_name":"Heike","last_name":"Trautmann","orcid":"0000-0002-9788-8282","full_name":"Trautmann, Heike","id":"100740"},{"full_name":"Mehnen, J","last_name":"Mehnen","first_name":"J"},{"first_name":"B","last_name":"Naujoks","full_name":"Naujoks, B"}],"year":"2010","title":"Sequential Parameter Optimisation for Multi-Objective Evolutionary Optimisation of Additive Layer Manufacturing","status":"public","date_updated":"2023-10-16T13:55:25Z","publisher":"Copyright C.O.C. Com. org. Conv.","_id":"46404","language":[{"iso":"eng"}],"editor":[{"last_name":"Teti","first_name":"R","full_name":"Teti, R"}],"user_id":"15504","citation":{"ama":"Ding J, Wessing S, Trautmann H, Mehnen J, Naujoks B. Sequential Parameter Optimisation for Multi-Objective Evolutionary Optimisation of Additive Layer Manufacturing. In: Teti R, ed. <i>Proceedings of the 7$^th$ CIRP International Seminar on Intelligent Computation in Manufacturing Engineering (CIRP ICME ’10)</i>. Copyright C.O.C. Com. org. Conv.; 2010.","bibtex":"@inproceedings{Ding_Wessing_Trautmann_Mehnen_Naujoks_2010, place={Capri, Italy}, title={Sequential Parameter Optimisation for Multi-Objective Evolutionary Optimisation of Additive Layer Manufacturing}, booktitle={Proceedings of the 7$^th$ CIRP International Seminar on Intelligent Computation in Manufacturing Engineering (CIRP ICME ’10)}, publisher={Copyright C.O.C. Com. org. Conv.}, author={Ding, J and Wessing, S and Trautmann, Heike and Mehnen, J and Naujoks, B}, editor={Teti, R}, year={2010} }","mla":"Ding, J., et al. “Sequential Parameter Optimisation for Multi-Objective Evolutionary Optimisation of Additive Layer Manufacturing.” <i>Proceedings of the 7$^th$ CIRP International Seminar on Intelligent Computation in Manufacturing Engineering (CIRP ICME ’10)</i>, edited by R Teti, Copyright C.O.C. Com. org. Conv., 2010.","short":"J. Ding, S. Wessing, H. Trautmann, J. Mehnen, B. Naujoks, in: R. Teti (Ed.), Proceedings of the 7$^th$ CIRP International Seminar on Intelligent Computation in Manufacturing Engineering (CIRP ICME ’10), Copyright C.O.C. Com. org. Conv., Capri, Italy, 2010.","chicago":"Ding, J, S Wessing, Heike Trautmann, J Mehnen, and B Naujoks. “Sequential Parameter Optimisation for Multi-Objective Evolutionary Optimisation of Additive Layer Manufacturing.” In <i>Proceedings of the 7$^th$ CIRP International Seminar on Intelligent Computation in Manufacturing Engineering (CIRP ICME ’10)</i>, edited by R Teti. Capri, Italy: Copyright C.O.C. Com. org. Conv., 2010.","apa":"Ding, J., Wessing, S., Trautmann, H., Mehnen, J., &#38; Naujoks, B. (2010). Sequential Parameter Optimisation for Multi-Objective Evolutionary Optimisation of Additive Layer Manufacturing. In R. Teti (Ed.), <i>Proceedings of the 7$^th$ CIRP International Seminar on Intelligent Computation in Manufacturing Engineering (CIRP ICME ’10)</i>. Copyright C.O.C. Com. org. Conv.","ieee":"J. Ding, S. Wessing, H. Trautmann, J. Mehnen, and B. Naujoks, “Sequential Parameter Optimisation for Multi-Objective Evolutionary Optimisation of Additive Layer Manufacturing,” in <i>Proceedings of the 7$^th$ CIRP International Seminar on Intelligent Computation in Manufacturing Engineering (CIRP ICME ’10)</i>, 2010."},"publication":"Proceedings of the 7$^th$ CIRP International Seminar on Intelligent Computation in Manufacturing Engineering (CIRP ICME ’10)","date_created":"2023-08-04T16:01:38Z","place":"Capri, Italy","department":[{"_id":"34"},{"_id":"819"}],"type":"conference"},{"place":"Berlin, Heidelberg","date_created":"2023-08-04T16:07:48Z","type":"conference","department":[{"_id":"34"},{"_id":"819"}],"publication":"Parallel Problem Solving from Nature, PPSN XI","citation":{"chicago":"Voß, Thomas, Heike Trautmann, and Christian Igel. “New Uncertainty Handling Strategies in Multi-Objective Evolutionary Optimization.” In <i>Parallel Problem Solving from Nature, PPSN XI</i>, edited by Robert Schaefer, Carlos Cotta, Joanna Kołodziej, and Günter Rudolph, 260–269. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. <a href=\"https://doi.org/10.1007/978-3-642-15871-1_27\">https://doi.org/10.1007/978-3-642-15871-1_27</a>.","short":"T. Voß, H. Trautmann, C. Igel, in: R. Schaefer, C. Cotta, J. Kołodziej, G. Rudolph (Eds.), Parallel Problem Solving from Nature, PPSN XI, Springer Berlin Heidelberg, Berlin, Heidelberg, 2010, pp. 260–269.","ieee":"T. Voß, H. Trautmann, and C. Igel, “New Uncertainty Handling Strategies in Multi-objective Evolutionary Optimization,” in <i>Parallel Problem Solving from Nature, PPSN XI</i>, 2010, pp. 260–269, doi: <a href=\"https://doi.org/10.1007/978-3-642-15871-1_27\">https://doi.org/10.1007/978-3-642-15871-1_27</a>.","apa":"Voß, T., Trautmann, H., &#38; Igel, C. (2010). New Uncertainty Handling Strategies in Multi-objective Evolutionary Optimization. In R. Schaefer, C. Cotta, J. Kołodziej, &#38; G. Rudolph (Eds.), <i>Parallel Problem Solving from Nature, PPSN XI</i> (pp. 260–269). Springer Berlin Heidelberg. <a href=\"https://doi.org/10.1007/978-3-642-15871-1_27\">https://doi.org/10.1007/978-3-642-15871-1_27</a>","bibtex":"@inproceedings{Voß_Trautmann_Igel_2010, place={Berlin, Heidelberg}, title={New Uncertainty Handling Strategies in Multi-objective Evolutionary Optimization}, DOI={<a href=\"https://doi.org/10.1007/978-3-642-15871-1_27\">https://doi.org/10.1007/978-3-642-15871-1_27</a>}, booktitle={Parallel Problem Solving from Nature, PPSN XI}, publisher={Springer Berlin Heidelberg}, author={Voß, Thomas and Trautmann, Heike and Igel, Christian}, editor={Schaefer, Robert and Cotta, Carlos and Kołodziej, Joanna and Rudolph, Günter}, year={2010}, pages={260–269} }","ama":"Voß T, Trautmann H, Igel C. New Uncertainty Handling Strategies in Multi-objective Evolutionary Optimization. In: Schaefer R, Cotta C, Kołodziej J, Rudolph G, eds. <i>Parallel Problem Solving from Nature, PPSN XI</i>. Springer Berlin Heidelberg; 2010:260–269. doi:<a href=\"https://doi.org/10.1007/978-3-642-15871-1_27\">https://doi.org/10.1007/978-3-642-15871-1_27</a>","mla":"Voß, Thomas, et al. “New Uncertainty Handling Strategies in Multi-Objective Evolutionary Optimization.” <i>Parallel Problem Solving from Nature, PPSN XI</i>, edited by Robert Schaefer et al., Springer Berlin Heidelberg, 2010, pp. 260–269, doi:<a href=\"https://doi.org/10.1007/978-3-642-15871-1_27\">https://doi.org/10.1007/978-3-642-15871-1_27</a>."},"abstract":[{"lang":"eng","text":"Since many real-world optimization problems are noisy, vector optimization algorithms that can cope with noise and uncertainty are required. We propose new, robust selection strategies for evolutionary multi-objective optimization in the presence of noise. We apply new measures of uncertainty for estimating the recently introduced Pareto-dominance for uncertain and noisy environments (PDU). The first measure is the inter-quartile range of the outcomes of repeated function evaluations. The second is based on axis-aligned bounding boxes around the upper and lower quantiles of the sampled fitness values in objective space. Experiments on real and artificial problems show promising results."}],"page":"260–269","language":[{"iso":"eng"}],"_id":"46409","publisher":"Springer Berlin Heidelberg","doi":"https://doi.org/10.1007/978-3-642-15871-1_27","user_id":"15504","editor":[{"full_name":"Schaefer, Robert","first_name":"Robert","last_name":"Schaefer"},{"full_name":"Cotta, Carlos","last_name":"Cotta","first_name":"Carlos"},{"first_name":"Joanna","last_name":"Kołodziej","full_name":"Kołodziej, Joanna"},{"first_name":"Günter","last_name":"Rudolph","full_name":"Rudolph, Günter"}],"title":"New Uncertainty Handling Strategies in Multi-objective Evolutionary Optimization","year":"2010","status":"public","author":[{"full_name":"Voß, Thomas","last_name":"Voß","first_name":"Thomas"},{"id":"100740","full_name":"Trautmann, Heike","orcid":"0000-0002-9788-8282","first_name":"Heike","last_name":"Trautmann"},{"full_name":"Igel, Christian","first_name":"Christian","last_name":"Igel"}],"publication_identifier":{"isbn":["978-3-642-15871-1"]},"date_updated":"2023-10-16T13:56:48Z"},{"date_updated":"2023-10-16T13:57:41Z","intvolume":"        14","title":"Integration of Preferences in Hypervolume-Based Multiobjective Evolutionary Algorithms by Means of Desirability Functions","status":"public","year":"2010","author":[{"last_name":"Wagner","first_name":"Tobias","full_name":"Wagner, Tobias"},{"orcid":"0000-0002-9788-8282","last_name":"Trautmann","first_name":"Heike","full_name":"Trautmann, Heike","id":"100740"}],"publication_identifier":{"issn":["1941-0026"]},"doi":"10.1109/TEVC.2010.2058119","user_id":"15504","volume":14,"page":"688-701","_id":"46412","language":[{"iso":"eng"}],"abstract":[{"lang":"eng","text":"In this paper, a concept for efficiently approximating the practically relevant regions of the Pareto front (PF) is introduced. Instead of the original objectives, desirability functions (DFs) of the objectives are optimized, which express the preferences of the decision maker. The original problem formulation and the optimization algorithm do not have to be modified. DFs map an objective to the domain [0, 1] and nonlinearly increase with better objective quality. By means of this mapping, values of different objectives and units become comparable. A biased distribution of the solutions in the PF approximation based on different scalings of the objectives is prevented. Thus, we propose the integration of DFs into the S-metric selection evolutionary multiobjective algorithm. The transformation ensures the meaning of the hypervolumes internally computed. Furthermore, it is shown that the reference point for the hypervolume calculation can be set intuitively. The approach is analyzed using standard test problems. Moreover, a practical validation by means of the optimization of a turning process is performed."}],"issue":"5","publication":"IEEE Transactions on Evolutionary Computation","citation":{"bibtex":"@article{Wagner_Trautmann_2010, title={Integration of Preferences in Hypervolume-Based Multiobjective Evolutionary Algorithms by Means of Desirability Functions}, volume={14}, DOI={<a href=\"https://doi.org/10.1109/TEVC.2010.2058119\">10.1109/TEVC.2010.2058119</a>}, number={5}, journal={IEEE Transactions on Evolutionary Computation}, author={Wagner, Tobias and Trautmann, Heike}, year={2010}, pages={688–701} }","ama":"Wagner T, Trautmann H. Integration of Preferences in Hypervolume-Based Multiobjective Evolutionary Algorithms by Means of Desirability Functions. <i>IEEE Transactions on Evolutionary Computation</i>. 2010;14(5):688-701. doi:<a href=\"https://doi.org/10.1109/TEVC.2010.2058119\">10.1109/TEVC.2010.2058119</a>","mla":"Wagner, Tobias, and Heike Trautmann. “Integration of Preferences in Hypervolume-Based Multiobjective Evolutionary Algorithms by Means of Desirability Functions.” <i>IEEE Transactions on Evolutionary Computation</i>, vol. 14, no. 5, 2010, pp. 688–701, doi:<a href=\"https://doi.org/10.1109/TEVC.2010.2058119\">10.1109/TEVC.2010.2058119</a>.","chicago":"Wagner, Tobias, and Heike Trautmann. “Integration of Preferences in Hypervolume-Based Multiobjective Evolutionary Algorithms by Means of Desirability Functions.” <i>IEEE Transactions on Evolutionary Computation</i> 14, no. 5 (2010): 688–701. <a href=\"https://doi.org/10.1109/TEVC.2010.2058119\">https://doi.org/10.1109/TEVC.2010.2058119</a>.","short":"T. Wagner, H. Trautmann, IEEE Transactions on Evolutionary Computation 14 (2010) 688–701.","ieee":"T. Wagner and H. Trautmann, “Integration of Preferences in Hypervolume-Based Multiobjective Evolutionary Algorithms by Means of Desirability Functions,” <i>IEEE Transactions on Evolutionary Computation</i>, vol. 14, no. 5, pp. 688–701, 2010, doi: <a href=\"https://doi.org/10.1109/TEVC.2010.2058119\">10.1109/TEVC.2010.2058119</a>.","apa":"Wagner, T., &#38; Trautmann, H. (2010). Integration of Preferences in Hypervolume-Based Multiobjective Evolutionary Algorithms by Means of Desirability Functions. <i>IEEE Transactions on Evolutionary Computation</i>, <i>14</i>(5), 688–701. <a href=\"https://doi.org/10.1109/TEVC.2010.2058119\">https://doi.org/10.1109/TEVC.2010.2058119</a>"},"type":"journal_article","department":[{"_id":"34"},{"_id":"819"}],"date_created":"2023-08-04T16:10:02Z"},{"date_created":"2023-08-04T16:09:19Z","type":"journal_article","keyword":["Roll cooling design","Uncertainty","Design optimisation","Multi-objective optimisation","Constraint in design"],"department":[{"_id":"34"},{"_id":"819"}],"issue":"4","publication":"CIRP Journal of Manufacturing Science and Technology","abstract":[{"text":"The paper presents a framework to optimise the design of work roll based on the cooling performance. The framework develops meta-models from a set of finite element analyses (FEA) of the roll cooling. A design of experiment technique is used to identify the FEA runs. The research also identifies sources of uncertainties in the design process. A robust evolutionary multi-objective evaluation technique is applied to the design optimisation in constrained problems with real life uncertainty. The approach handles uncertainties associated both with design variables and fitness functions. Constraints violation within the neighbourhood of a design is considered as part of a measurement for degree of feasibility and robustness of a solution.","lang":"eng"}],"language":[{"iso":"eng"}],"doi":"https://doi.org/10.1016/j.cirpj.2010.06.001","title":"Work roll cooling system design optimisation in presence of uncertainty and constrains","year":"2010","author":[{"full_name":"Azene, Y.T.","first_name":"Y.T.","last_name":"Azene"},{"full_name":"Roy, R.","last_name":"Roy","first_name":"R."},{"first_name":"D.","last_name":"Farrugia","full_name":"Farrugia, D."},{"full_name":"Onisa, C.","last_name":"Onisa","first_name":"C."},{"last_name":"Mehnen","first_name":"J.","full_name":"Mehnen, J."},{"id":"100740","full_name":"Trautmann, Heike","orcid":"0000-0002-9788-8282","first_name":"Heike","last_name":"Trautmann"}],"publication_identifier":{"issn":["1755-5817"]},"date_updated":"2023-10-16T13:57:23Z","intvolume":"         2","citation":{"apa":"Azene, Y. T., Roy, R., Farrugia, D., Onisa, C., Mehnen, J., &#38; Trautmann, H. (2010). Work roll cooling system design optimisation in presence of uncertainty and constrains. <i>CIRP Journal of Manufacturing Science and Technology</i>, <i>2</i>(4), 290–298. <a href=\"https://doi.org/10.1016/j.cirpj.2010.06.001\">https://doi.org/10.1016/j.cirpj.2010.06.001</a>","mla":"Azene, Y. T., et al. “Work Roll Cooling System Design Optimisation in Presence of Uncertainty and Constrains.” <i>CIRP Journal of Manufacturing Science and Technology</i>, vol. 2, no. 4, 2010, pp. 290–98, doi:<a href=\"https://doi.org/10.1016/j.cirpj.2010.06.001\">https://doi.org/10.1016/j.cirpj.2010.06.001</a>.","ieee":"Y. T. Azene, R. Roy, D. Farrugia, C. Onisa, J. Mehnen, and H. Trautmann, “Work roll cooling system design optimisation in presence of uncertainty and constrains,” <i>CIRP Journal of Manufacturing Science and Technology</i>, vol. 2, no. 4, pp. 290–298, 2010, doi: <a href=\"https://doi.org/10.1016/j.cirpj.2010.06.001\">https://doi.org/10.1016/j.cirpj.2010.06.001</a>.","chicago":"Azene, Y.T., R. Roy, D. Farrugia, C. Onisa, J. Mehnen, and Heike Trautmann. “Work Roll Cooling System Design Optimisation in Presence of Uncertainty and Constrains.” <i>CIRP Journal of Manufacturing Science and Technology</i> 2, no. 4 (2010): 290–98. <a href=\"https://doi.org/10.1016/j.cirpj.2010.06.001\">https://doi.org/10.1016/j.cirpj.2010.06.001</a>.","ama":"Azene YT, Roy R, Farrugia D, Onisa C, Mehnen J, Trautmann H. Work roll cooling system design optimisation in presence of uncertainty and constrains. <i>CIRP Journal of Manufacturing Science and Technology</i>. 2010;2(4):290-298. doi:<a href=\"https://doi.org/10.1016/j.cirpj.2010.06.001\">https://doi.org/10.1016/j.cirpj.2010.06.001</a>","short":"Y.T. Azene, R. Roy, D. Farrugia, C. Onisa, J. Mehnen, H. Trautmann, CIRP Journal of Manufacturing Science and Technology 2 (2010) 290–298.","bibtex":"@article{Azene_Roy_Farrugia_Onisa_Mehnen_Trautmann_2010, title={Work roll cooling system design optimisation in presence of uncertainty and constrains}, volume={2}, DOI={<a href=\"https://doi.org/10.1016/j.cirpj.2010.06.001\">https://doi.org/10.1016/j.cirpj.2010.06.001</a>}, number={4}, journal={CIRP Journal of Manufacturing Science and Technology}, author={Azene, Y.T. and Roy, R. and Farrugia, D. and Onisa, C. and Mehnen, J. and Trautmann, Heike}, year={2010}, pages={290–298} }"},"page":"290-298","_id":"46411","user_id":"15504","volume":2,"status":"public"}]
