{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T10:32:49Z","timestamp":1783765969724,"version":"3.55.0"},"publisher-location":"Cham","reference-count":27,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030870935","type":"print"},{"value":"9783030870942","type":"electronic"}],"license":[{"start":{"date-parts":[[2021,11,18]],"date-time":"2021-11-18T00:00:00Z","timestamp":1637193600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,11,18]],"date-time":"2021-11-18T00:00:00Z","timestamp":1637193600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-030-87094-2_7","type":"book-chapter","created":{"date-parts":[[2021,11,17]],"date-time":"2021-11-17T07:06:45Z","timestamp":1637132805000},"page":"71-82","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Avoiding Excess Computation in Asynchronous Evolutionary Algorithms"],"prefix":"10.1007","author":[{"given":"Eric O.","family":"Scott","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mark","family":"Coletti","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Catherine D.","family":"Schuman","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bill","family":"Kay","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shruti R.","family":"Kulkarni","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maryam","family":"Parsa","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kenneth A.","family":"De Jong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,11,18]]},"reference":[{"key":"7_CR1","doi-asserted-by":"publisher","DOI":"10.1002\/0471739383","volume-title":"Parallel Metaheuristics: A New Class of Algorithms","author":"E Alba","year":"2005","unstructured":"Alba, E.: Parallel Metaheuristics: A New Class of Algorithms, vol. 47. Wiley, Hoboken (2005)"},{"key":"7_CR2","doi-asserted-by":"crossref","unstructured":"Chai, Z., et al.: FedAT: a communication-efficient federated learning method with asynchronous tiers under non-IID data. arXiv preprint arXiv:2010.05958 (2020)","DOI":"10.1145\/3458817.3476211"},{"key":"7_CR3","doi-asserted-by":"crossref","unstructured":"Chen, Y., et al.: Asynchronous online federated learning for edge devices with non-IID data. In: 2020 IEEE International Conference on Big Data (Big Data), pp. 15\u201324. IEEE (2020)","DOI":"10.1109\/BigData50022.2020.9378161"},{"key":"7_CR4","doi-asserted-by":"crossref","unstructured":"Churchill, A.W., Husbands, P., Philippides, A.: Tool sequence optimization using synchronous and asynchronous parallel multi-objective evolutionary algorithms with heterogeneous evaluations. In: IEEE Congress on Evolutionary Computation, pp. 2924\u20132931. IEEE (2013)","DOI":"10.1109\/CEC.2013.6557925"},{"issue":"3\/4","key":"7_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1147\/JRD.2019.2960225","volume":"64","author":"M Coletti","year":"2019","unstructured":"Coletti, M., Fafard, A., Page, D.: Troubleshooting deep-learner training data problems using an evolutionary algorithm on summit. IBM J. Res. Dev. 64(3\/4), 1\u201312 (2019)","journal-title":"IBM J. Res. Dev."},{"key":"7_CR6","doi-asserted-by":"crossref","unstructured":"Coletti, M.A., Scott, E.O., Bassett, J.K.: Library for evolutionary algorithms in python (LEAP). In: Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion, pp. 1571\u20131579 (2020)","DOI":"10.1145\/3377929.3398147"},{"key":"7_CR7","unstructured":"D\u2019Auria, M., et al.: Distributed, automated calibration of agent-based model parameters and agent behaviors. In: Autonomous Agents and Multiagent Systems (AAMAS) (2020)"},{"key":"7_CR8","volume-title":"Evolutionary Computation: A Unified Approach","author":"KA De Jong","year":"2006","unstructured":"De Jong, K.A.: Evolutionary Computation: A Unified Approach. MIT Press, Cambridge (2006)"},{"issue":"2","key":"7_CR9","doi-asserted-by":"publisher","first-page":"261","DOI":"10.1162\/EVCO_a_00076","volume":"21","author":"M Depolli","year":"2013","unstructured":"Depolli, M., Trobec, R., Filipi\u010d, B.: Asynchronous master-slave parallelization of differential evolution for multi-objective optimization. Evol. Comput. 21(2), 261\u2013291 (2013)","journal-title":"Evol. Comput."},{"key":"7_CR10","doi-asserted-by":"crossref","unstructured":"Durillo, J.J.: A study of master-slave approaches to parallelize NSGA-II. In: IEEE International Symposium on Parallel and Distributed Processing, pp. 1\u20138. IEEE (2008)","DOI":"10.1109\/IPDPS.2008.4536375"},{"key":"7_CR11","doi-asserted-by":"crossref","unstructured":"Gunaratne, C., Garibay, I.: Evolutionary model discovery of causal factors behind the socio-agricultural behavior of the ancestral pueblo. Plos One 15(12), e0239922 (2020)","DOI":"10.1371\/journal.pone.0239922"},{"key":"7_CR12","doi-asserted-by":"crossref","unstructured":"Harada, T.: Mathematical model of asynchronous parallel evolutionary algorithm to analyze influence of evaluation time bias. In: 2019 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE), pp. 1\u20138. IEEE (2019)","DOI":"10.1109\/CSDE48274.2019.9162360"},{"key":"7_CR13","unstructured":"Jaderberg, M., et al.: Population based training of neural networks. arXiv preprint arXiv:1711.09846 (2017)"},{"key":"7_CR14","unstructured":"Kim, J.: Hierarchical asynchronous genetic algorithms for parallel\/distributed simulation-based optimization (1994)"},{"key":"7_CR15","unstructured":"Lee, K., et al.: An efficient asynchronous method for integrating evolutionary and gradient-based policy search. In: Advances in Neural Information Processing Systems, vol. 33 (2020)"},{"key":"7_CR16","unstructured":"McMahan, B., et al.: Communication-efficient learning of deep networks from decentralized data. In: Artificial Intelligence and Statistics, pp. 1273\u20131282. PMLR (2017)"},{"key":"7_CR17","doi-asserted-by":"crossref","unstructured":"Parker Mitchell, J., Schuman, C.D., Potok, T.E.: A small, low cost event-driven architecture for spiking neural networks on FPGAs. In: International Conference on Neuromorphic Systems, pp. 1\u20134 (2020)","DOI":"10.1145\/3407197.3407216"},{"key":"7_CR18","unstructured":"O\u2019Kelly, M., et al.: F1Tenth: an open-source evaluation environment for continuous control and reinforcement learning. In: Proceedings of Machine Learning Research, vol. 123 (2020)"},{"key":"7_CR19","doi-asserted-by":"publisher","first-page":"161551","DOI":"10.1109\/ACCESS.2020.3021192","volume":"8","author":"A Pellegrini","year":"2020","unstructured":"Pellegrini, A., et al.: Simulation-based evolutionary optimization of air traffic management. IEEE Access 8, 161551\u2013161570 (2020)","journal-title":"IEEE Access"},{"key":"7_CR20","doi-asserted-by":"crossref","unstructured":"Rasheed, K., Davison, B.D.: Effect of global parallelism on the behavior of a steady state genetic algorithm for design optimization. In: Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406), vol. 1, pp. 534\u2013541. IEEE (1999)","DOI":"10.1109\/CEC.1999.781979"},{"key":"7_CR21","doi-asserted-by":"crossref","unstructured":"Scott, E.O., De Jong, K.A.: Evaluation-time bias in quasi-generational and steady-state asynchronous evolutionary algorithms. In: Proceedings of the Genetic and Evolutionary Computation Conference, pp. 845\u2013852 (2016)","DOI":"10.1145\/2908812.2908934"},{"key":"7_CR22","doi-asserted-by":"crossref","unstructured":"Scott, E.O., De Jong, K.A.: Understanding simple asynchronous evolutionary algorithms. In: Proceedings of the 2015 ACM Conference on Foundations of Genetic Algorithms XIII, pp. 85\u201398 (2015)","DOI":"10.1145\/2725494.2725509"},{"key":"7_CR23","unstructured":"Stanley, T.J., Mudge, T.N.: A parallel genetic algorithm for multiobjective microprocessor design. In: ICGA, pp. 597\u2013604. Citeseer (1995)"},{"key":"7_CR24","unstructured":"Darrell Whitley, L.: The genitor algorithm and selection pressure: why rank-based allocation of reproductive trials is best. In: International Conference on Genetic Algorithms, Fairfax, VA, vol. 89, pp. 116\u2013123 (1989)"},{"key":"7_CR25","doi-asserted-by":"crossref","unstructured":"Xia, Q., Ye, W., Tao, Z., Wu, J., Li, Q.: A survey of federated learning for edge computing: research problems and solutions. In: High-Confidence Computing, p. 100008 (2021)","DOI":"10.1016\/j.hcc.2021.100008"},{"key":"7_CR26","doi-asserted-by":"crossref","unstructured":"Yagoubi, M., Thobois, L., Schoenauer, M.: Asynchronous evolutionary multi-objective algorithms with heterogeneous evaluation costs. In: 2011 IEEE Congress of Evolutionary Computation (CEC), pp. 21\u201328. IEEE (2011)","DOI":"10.1109\/CEC.2011.5949593"},{"key":"7_CR27","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"122","DOI":"10.1007\/978-3-642-38610-7_12","volume-title":"Artificial Intelligence and Soft Computing","author":"A-C Z\u0103voianu","year":"2013","unstructured":"Z\u0103voianu, A.-C., Lughofer, E., Koppelst\u00e4tter, W., Weidenholzer, G., Amrhein, W., Klement, E.P.: On the performance of master-slave parallelization methods for multi-objective evolutionary algorithms. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2013. LNCS (LNAI), vol. 7895, pp. 122\u2013134. Springer, Heidelberg (2013). https:\/\/doi.org\/10.1007\/978-3-642-38610-7_12"}],"container-title":["Advances in Intelligent Systems and Computing","Advances in Computational Intelligence Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-87094-2_7","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,12]],"date-time":"2024-09-12T10:21:18Z","timestamp":1726136478000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-87094-2_7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11,18]]},"ISBN":["9783030870935","9783030870942"],"references-count":27,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-87094-2_7","relation":{},"ISSN":["2194-5357","2194-5365"],"issn-type":[{"value":"2194-5357","type":"print"},{"value":"2194-5365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,11,18]]},"assertion":[{"value":"18 November 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"UKCI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"UK Workshop on Computational Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Aberystwyth","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"United Kingdom","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 September 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 September 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ukci2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ukci2021.dcs.aber.ac.uk\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}