{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T05:02:48Z","timestamp":1750309368620,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":36,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,7,14]],"date-time":"2024-07-14T00:00:00Z","timestamp":1720915200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,7,14]]},"DOI":"10.1145\/3638530.3664133","type":"proceedings-article","created":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T14:54:43Z","timestamp":1722524083000},"page":"1715-1723","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Modular Optimization Framework for Mixed Expensive and Inexpensive Real-World Problems"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0865-4709","authenticated-orcid":false,"given":"Roy","family":"de Winter","sequence":"first","affiliation":[{"name":"Leiden University, Leiden, Netherlands"},{"name":"C-Job Naval Architects, Hoofddorp, Netherlands"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6768-1478","authenticated-orcid":false,"given":"Thomas","family":"B\u00e4ck","sequence":"additional","affiliation":[{"name":"Leiden University, Leiden, Netherlands"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0013-7969","authenticated-orcid":false,"given":"Niki","family":"Van Stein","sequence":"additional","affiliation":[{"name":"Leiden University, Leiden, Netherlands"}]}],"member":"320","published-online":{"date-parts":[[2024,8]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Batch Bayesian optimization via simulation matching. Advances in neural information processing systems 23","author":"Azimi Javad","year":"2010","unstructured":"Javad Azimi, Alan Fern, and Xiaoli Fern. 2010. Batch Bayesian optimization via simulation matching. Advances in neural information processing systems 23 (2010), 109--117."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1162\/evco_a_00325"},{"key":"e_1_3_2_1_3_1","volume-title":"Proc. 27. Workshop Computational Intelligence, F. Hoffmann, E. H\u00fcllermeier, and R. Mikut (Eds.). Universit\u00e4tsverlag Karlsruhe, Universit\u00e4t Munchen, 243--259","author":"Bagheri Samineh","year":"2017","unstructured":"Samineh Bagheri, Wolfgang Konen, and Thomas B\u00e4ck. 2017. Comparing kriging and radial basis function surrogates. In Proc. 27. Workshop Computational Intelligence, F. Hoffmann, E. H\u00fcllermeier, and R. Mikut (Eds.). Universit\u00e4tsverlag Karlsruhe, Universit\u00e4t Munchen, 243--259."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2017.07.060"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-72062-9_21"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3377930.3390155"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511543241"},{"key":"e_1_3_2_1_8_1","unstructured":"C-Job Naval Architects. 2023. Saronic Ferries. https:\/\/c-job.com\/projects\/saronic-ferries\/"},{"key":"e_1_3_2_1_9_1","unstructured":"C-Job Naval Architects. 2023. Saronic Ferries Partners With C-Job Naval Architects for the Design of the First Fully-Electric Ro-Pax Ferry in Greece. https:\/\/c-job.com\/press\/saronic-ferries-partners-with-c-job-naval-architects-for-the-design-of-the-first-fully-electric-ro-pax-ferry-in-greece\/"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.5957\/jsr.2006.50.1.1"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3520304.3533640"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3449726.3463167"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12293-022-00363-y"},{"key":"e_1_3_2_1_14_1","volume-title":"A fast and elitist multiobjective genetic algorithm: NSGA-II","author":"Deb Kalyanmoy","year":"2002","unstructured":"Kalyanmoy Deb, Amrit Pratap, Sameer Agarwal, and TAMT Meyarivan. 2002. A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE transactions on evolutionary computation 6, 2 (2002), 182--197."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/3449726.3463276"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.advengsoft.2011.05.014"},{"volume-title":"A collection of test problems for constrained global optimization algorithms","author":"Floudas Christodoulos A","key":"e_1_3_2_1_17_1","unstructured":"Christodoulos A Floudas and Panos M Pardalos. 1990. A collection of test problems for constrained global optimization algorithms. Springer."},{"key":"e_1_3_2_1_18_1","volume-title":"A tutorial on Bayesian optimization. arXiv preprint arXiv:1807.02811","author":"Frazier Peter I","year":"2018","unstructured":"Peter I Frazier. 2018. A tutorial on Bayesian optimization. arXiv preprint arXiv:1807.02811 (2018)."},{"key":"e_1_3_2_1_19_1","unstructured":"Manolis Georgioudakis. 2017. PyDE. https:\/\/github.com\/geoem\/pyDE\/tree\/master"},{"key":"e_1_3_2_1_20_1","volume-title":"Powerful Ship Hull Design in Rhino with Rapid Hull Modeling Methodology","author":"Petersen Gerard","year":"2009","unstructured":"Gerard Petersen. 2015. Powerful Ship Hull Design in Rhino with Rapid Hull Modeling Methodology. Rhino Centre. http:\/\/rhinocentre.blogspot.com\/2009\/11\/rhino-rapid-hull-modeling-methodology.html"},{"key":"e_1_3_2_1_21_1","unstructured":"Javier Gonz\u00e1lez Zhenwen Dai Philipp Hennig and Neil Lawrence. 2016. Batch Bayesian optimization via local penalization. In Artificial intelligence and statistics. PMLR 648--657."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1007\/BF01386213"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1008306431147"},{"key":"e_1_3_2_1_24_1","first-page":"8","article-title":"Problem definitions and evaluation criteria for the CEC 2006 special session on constrained real-parameter optimization","volume":"41","author":"Liang Jing J","year":"2006","unstructured":"Jing J Liang, Thomas Philip Runarsson, Efren Mezura-Montes, Maurice Clerc, Ponnuthurai Nagaratnam Suganthan, CA Coello Coello, and Kalyanmoy Deb. 2006. Problem definitions and evaluation criteria for the CEC 2006 special session on constrained real-parameter optimization. Journal of Applied Mechanics 41, 8 (2006), 8--31.","journal-title":"Journal of Applied Mechanics"},{"key":"e_1_3_2_1_25_1","volume-title":"International Conference on Swarm Intelligence. Springer, Springer, 95--106","author":"L\u00f3pez-Ib\u00e1\u00f1ez Manuel","year":"2010","unstructured":"Manuel L\u00f3pez-Ib\u00e1\u00f1ez and Thomas St\u00fctzle. 2010. Automatic configuration of multi-objective ACO algorithms. In International Conference on Swarm Intelligence. Springer, Springer, 95--106."},{"volume-title":"Clustered multiple generalized expected improvement: A novel infill sampling criterion for surrogate models. In 2008 IEEE congress on evolutionary computation","author":"Ponweiser Wolfgang","key":"e_1_3_2_1_26_1","unstructured":"Wolfgang Ponweiser, Tobias Wagner, and Markus Vincze. 2008. Clustered multiple generalized expected improvement: A novel infill sampling criterion for surrogate models. In 2008 IEEE congress on evolutionary computation (IEEE world congress on computational intelligence). IEEE, IEEE, 3515--3522."},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-94-015-8330-5_4"},{"key":"e_1_3_2_1_28_1","volume-title":"version","author":"Industries Software Siemens Digital","year":"2021","unstructured":"Siemens Digital Industries Software. 2021. Simcenter STAR-CCM+ User Guide, version 2021.1. In Adaptive Mesh Refinement for Overset Meshes. Siemens, 3067--3070. https:\/\/docs.sw.siemens.com\/documentation\/external\/PL20200805113346338\/en-US\/userManual\/userguide\/html\/STARCCMP\/GUID-28A739CF-6DE2-4D87-B582-E390B522011C.html#"},{"volume-title":"An experimental investigation for resistance reduction on displacement-type ships by parabolization of hull form at waterline. Ph. D. Dissertation","author":"Tan Beng-Yeow","key":"e_1_3_2_1_29_1","unstructured":"Beng-Yeow Tan. 2004. An experimental investigation for resistance reduction on displacement-type ships by parabolization of hull form at waterline. Ph. D. Dissertation. University of British Columbia."},{"volume-title":"Many-Criteria Optimization and Decision Analysis: State-of-the-Art, Present Challenges, and Future Perspectives","author":"van der Blom Koen","key":"e_1_3_2_1_30_1","unstructured":"Koen van der Blom, Timo M Deist, Vanessa Volz, Mariapia Marchi, Yusuke Nojima, Boris Naujoks, Akira Oyama, and Tea Tu\u0161ar. 2023. Identifying properties of real-world optimisation problems through a questionnaire. In Many-Criteria Optimization and Decision Analysis: State-of-the-Art, Present Challenges, and Future Perspectives. Springer, 59--80."},{"key":"e_1_3_2_1_31_1","unstructured":"Niki van Stein Diederick Vermetten Anna V. Kononova and Thomas B\u00e4ck. 2024. Explainable Benchmarking for Iterative Optimization Heuristics. arXiv:2401.17842 [cs.NE]"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/3583131.3590417"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1080\/03052150410001686486"},{"key":"e_1_3_2_1_34_1","volume-title":"Maximizing acquisition functions for Bayesian optimization. Advances in neural information processing systems 31","author":"Wilson James","year":"2018","unstructured":"James Wilson, Frank Hutter, and Marc Deisenroth. 2018. Maximizing acquisition functions for Bayesian optimization. Advances in neural information processing systems 31 (2018), 9884--9895."},{"key":"e_1_3_2_1_35_1","volume-title":"The parallel knowledge gradient method for batch Bayesian optimization. Advances in neural information processing systems 29","author":"Wu Jian","year":"2016","unstructured":"Jian Wu and Peter Frazier. 2016. The parallel knowledge gradient method for batch Bayesian optimization. Advances in neural information processing systems 29 (2016), 3126--3134."},{"key":"e_1_3_2_1_36_1","volume-title":"Kay Chen Tan, and Ke Li","author":"Zhang Huan","year":"2023","unstructured":"Huan Zhang, Jinliang Ding, Liang Feng, Kay Chen Tan, and Ke Li. 2023. Solving Expensive Optimization Problems in Dynamic Environments with Meta-learning. arXiv preprint arXiv:2310.12538 (2023)."}],"event":{"name":"GECCO '24 Companion: Genetic and Evolutionary Computation Conference Companion","sponsor":["SIGEVO ACM Special Interest Group on Genetic and Evolutionary Computation"],"location":"Melbourne VIC Australia","acronym":"GECCO '24 Companion"},"container-title":["Proceedings of the Genetic and Evolutionary Computation Conference Companion"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3638530.3664133","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3638530.3664133","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T00:06:12Z","timestamp":1750291572000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3638530.3664133"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7,14]]},"references-count":36,"alternative-id":["10.1145\/3638530.3664133","10.1145\/3638530"],"URL":"https:\/\/doi.org\/10.1145\/3638530.3664133","relation":{},"subject":[],"published":{"date-parts":[[2024,7,14]]},"assertion":[{"value":"2024-08-01","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}