{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T09:11:23Z","timestamp":1758273083324,"version":"3.40.3"},"publisher-location":"Cham","reference-count":24,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030581145"},{"type":"electronic","value":"9783030581152"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-58115-2_44","type":"book-chapter","created":{"date-parts":[[2020,9,1]],"date-time":"2020-09-01T22:02:51Z","timestamp":1598997771000},"page":"634-647","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Analysis on the Efficiency of Multifactorial Evolutionary Algorithms"],"prefix":"10.1007","author":[{"given":"Zhengxin","family":"Huang","sequence":"first","affiliation":[]},{"given":"Zefeng","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Yuren","family":"Zhou","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,9,2]]},"reference":[{"issue":"1","key":"44_CR1","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1109\/4235.585888","volume":"1","author":"T Back","year":"1997","unstructured":"Back, T., Hammel, U., Schwefel, H.P.: Evolutionary computation: comments on the history and current state. IEEE Trans. Evol. Comput. 1(1), 3\u201317 (1997)","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"1","key":"44_CR2","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1109\/TEVC.2019.2906927","volume":"24","author":"KK Bali","year":"2020","unstructured":"Bali, K.K., Ong, Y.S., Gupta, A., Tan, P.S.: Multifactorial evolutionary algorithm with online transfer parameter estimation: MFEA-II. IEEE Trans. Evol. Comput. 24(1), 69\u201383 (2020)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"44_CR3","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"130","DOI":"10.1007\/978-3-319-94472-2_10","volume-title":"Services \u2013 SERVICES 2018","author":"L Bao","year":"2018","unstructured":"Bao, L., et al.: An evolutionary multitasking algorithm for cloud computing service composition. In: Yang, A., et al. (eds.) SERVICES 2018. LNCS, vol. 10975, pp. 130\u2013144. Springer, Cham (2018). \n                    https:\/\/doi.org\/10.1007\/978-3-319-94472-2_10"},{"key":"44_CR4","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1007\/978-3-319-46672-9_5","volume-title":"Neural Information Processing","author":"R Chandra","year":"2016","unstructured":"Chandra, R., Gupta, A., Ong, Y.-S., Goh, C.-K.: Evolutionary multi-task learning for modular training of feedforward neural networks. In: Hirose, A., Ozawa, S., Doya, K., Ikeda, K., Lee, M., Liu, D. (eds.) ICONIP 2016. LNCS, vol. 9948, pp. 37\u201346. Springer, Cham (2016). \n                    https:\/\/doi.org\/10.1007\/978-3-319-46672-9_5"},{"issue":"3","key":"44_CR5","doi-asserted-by":"publisher","first-page":"993","DOI":"10.1007\/s11063-017-9718-z","volume":"47","author":"R Chandra","year":"2018","unstructured":"Chandra, R., Gupta, A., Ong, Y.S., Goh, C.K.: Evolutionary multi-task learning for modular knowledge representation in neural networks. Neural Process. Lett. 47(3), 993\u20131009 (2018). \n                    https:\/\/doi.org\/10.1007\/s11063-017-9718-z","journal-title":"Neural Process. Lett."},{"issue":"2","key":"44_CR6","first-page":"176","volume":"31","author":"CR Cloninger","year":"1979","unstructured":"Cloninger, C.R., Rice, J., Reich, T.: Multifactorial inheritance with cultural transmission and assortative mating. ii. a general model of combined polygenic and cultural inheritance. Am. J. Hum. Genet. 31(2), 176 (1979)","journal-title":"Am. J. Hum. Genet."},{"issue":"3","key":"44_CR7","doi-asserted-by":"publisher","first-page":"484","DOI":"10.1109\/TEVC.2017.2724201","volume":"22","author":"DC Dang","year":"2018","unstructured":"Dang, D.C., et al.: Escaping local optima using crossover with emergent diversity. IEEE Trans. Evol. Comput. 22(3), 484\u2013497 (2018)","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"1","key":"44_CR8","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1109\/TEVC.2017.2785351","volume":"23","author":"J Ding","year":"2019","unstructured":"Ding, J., Yang, C., Jin, Y., Chai, T.: Generalized multitasking for evolutionary optimization of expensive problems. IEEE Trans. Evol. Comput. 23(1), 44\u201358 (2019)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"44_CR9","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1016\/j.tcs.2014.11.028","volume":"567","author":"B Doerr","year":"2015","unstructured":"Doerr, B., Doerr, C., Ebel, F.: From black-box complexity to designing new genetic algorithms. Theor. Comput. Sci. 567, 87\u2013104 (2015)","journal-title":"Theor. Comput. Sci."},{"issue":"11","key":"44_CR10","doi-asserted-by":"publisher","first-page":"453","DOI":"10.1016\/0169-5347(96)10052-5","volume":"11","author":"MW Feldman","year":"1996","unstructured":"Feldman, M.W., Laland, K.N.: Gene-culture coevolutionary theory. Trends Ecol. Evol. 11(11), 453\u2013457 (1996)","journal-title":"Trends Ecol. Evol."},{"key":"44_CR11","doi-asserted-by":"crossref","unstructured":"Feng, L., et al.: Solving generalized vehicle routing problem with occasional drivers via evolutionary multitasking. IEEE Trans. Cybern. (2020, in press)","DOI":"10.1109\/TCYB.2019.2955599"},{"issue":"9","key":"44_CR12","doi-asserted-by":"publisher","first-page":"3457","DOI":"10.1109\/TCYB.2018.2845361","volume":"49","author":"L Feng","year":"2018","unstructured":"Feng, L., et al.: Evolutionary multitasking via explicit autoencoding. IEEE Trans. Cybern. 49(9), 3457\u20133470 (2018)","journal-title":"IEEE Trans. Cybern."},{"issue":"3","key":"44_CR13","doi-asserted-by":"publisher","first-page":"343","DOI":"10.1109\/TEVC.2015.2458037","volume":"20","author":"A Gupta","year":"2016","unstructured":"Gupta, A., Ong, Y.S., Feng, L.: Multifactorial evolution: toward evolutionary multitasking. IEEE Trans. Evol. Comput. 20(3), 343\u2013357 (2016)","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"1","key":"44_CR14","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1016\/S0004-3702(01)00058-3","volume":"127","author":"J He","year":"2001","unstructured":"He, J., Yao, X.: Drift analysis and average time complexity of evolutionary algorithms. Artif. Intell. 127(1), 57\u201385 (2001)","journal-title":"Artif. Intell."},{"key":"44_CR15","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-17339-4","volume-title":"Analyzing evolutionary algorithms: the computer science perspective","author":"T Jansen","year":"2013","unstructured":"Jansen, T.: Analyzing evolutionary algorithms: the computer science perspective. Springer, Heidelberg (2013). \n                    https:\/\/doi.org\/10.1007\/978-3-642-17339-4"},{"key":"44_CR16","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"92","DOI":"10.1007\/978-3-319-99259-4_8","volume-title":"Parallel Problem Solving from Nature \u2013 PPSN XV","author":"T K\u00f6tzing","year":"2018","unstructured":"K\u00f6tzing, T., Krejca, M.S.: First-hitting times under additive drift. In: Auger, A., Fonseca, C.M., Louren\u00e7o, N., Machado, P., Paquete, L., Whitley, D. (eds.) PPSN 2018. LNCS, vol. 11102, pp. 92\u2013104. Springer, Cham (2018). \n                    https:\/\/doi.org\/10.1007\/978-3-319-99259-4_8"},{"key":"44_CR17","doi-asserted-by":"publisher","first-page":"1555","DOI":"10.1016\/j.ins.2019.10.066","volume":"512","author":"G Li","year":"2020","unstructured":"Li, G., Lin, Q., Gao, W.: Multifactorial optimization via explicit multipopulation evolutionary framework. Inf. Sci. 512, 1555\u20131570 (2020)","journal-title":"Inf. Sci."},{"issue":"5","key":"44_CR18","doi-asserted-by":"publisher","first-page":"733","DOI":"10.1109\/TEVC.2018.2881955","volume":"23","author":"H Li","year":"2019","unstructured":"Li, H., Ong, Y., Gong, M., Wang, Z.: Evolutionary multitasking sparse reconstruction: framework and case study. IEEE Trans. Evol. Comput. 23(5), 733\u2013747 (2019)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"44_CR19","doi-asserted-by":"crossref","unstructured":"Liaw, R.T., Ting, C.K.: Evolutionary many tasking optimization based on symbiosis in biocoenosis. In: The Thirty-Third AAAI Conference on Artificial Intelligence, AAAI, pp. 4295\u20134303 (2019)","DOI":"10.1609\/aaai.v33i01.33014295"},{"key":"44_CR20","doi-asserted-by":"crossref","unstructured":"Lin, J., Liu, H.L., Xue, B., Zhang, M., Gu, F.: Multi-objective multi-tasking optimization based on incremental learning. IEEE Trans. Evol. Comput. (2020, in press)","DOI":"10.1109\/TEVC.2019.2962747"},{"key":"44_CR21","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-16544-3","volume-title":"Bioinspired Computation in Combinatorial Optimization - Algorithms and Their Computational Complexity","author":"F Neumann","year":"2010","unstructured":"Neumann, F., Witt, C.: Bioinspired Computation in Combinatorial Optimization - Algorithms and Their Computational Complexity. Springer, Heidelberg (2010). \n                    https:\/\/doi.org\/10.1007\/978-3-642-16544-3"},{"key":"44_CR22","doi-asserted-by":"publisher","first-page":"279","DOI":"10.1016\/j.artint.2019.06.005","volume":"275","author":"C Qian","year":"2019","unstructured":"Qian, C., Yu, Y., Tang, K., Yao, X., Zhou, Z.H.: Maximizing submodular or monotone approximately submodular functions by multi-objective evolutionary algorithms. Artif. Intell. 275, 279\u2013294 (2019)","journal-title":"Artif. Intell."},{"key":"44_CR23","doi-asserted-by":"crossref","unstructured":"Tang, J., Chen, Y., Deng, Z., Xiang, Y., Joy, C.P.: A group-based approach to improve multifactorial evolutionary algorithm. In: International Joint Conference on Artificial Intelligence, IJCAI, pp. 3870\u20133876 (2018)","DOI":"10.24963\/ijcai.2018\/538"},{"key":"44_CR24","unstructured":"Zhou, L., Feng, L., Zhong, J., Ong, Y.S., Zhu, Z., Sha, E.: Evolutionary multitasking in combinatorial search spaces: a case study in capacitated vehicle routing problem. In: IEEE Symposium Series on Computational Intelligence (SSCI), pp. 1\u20138. IEEE (2016)"}],"container-title":["Lecture Notes in Computer Science","Parallel Problem Solving from Nature \u2013 PPSN XVI"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-58115-2_44","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,9,2]],"date-time":"2020-09-02T04:17:55Z","timestamp":1599020275000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-58115-2_44"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030581145","9783030581152"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-58115-2_44","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"2 September 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PPSN","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Parallel Problem Solving from Nature","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Leiden","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"The Netherlands","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 September 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9 September 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ppsn2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ppsn2020.liacs.leidenuniv.nl\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Easychair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"268","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"99","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"37% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2.2","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}