{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T16:47:36Z","timestamp":1743094056103,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":24,"publisher":"Springer Singapore","isbn-type":[{"type":"print","value":"9789811534249"},{"type":"electronic","value":"9789811534256"}],"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"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-981-15-3425-6_17","type":"book-chapter","created":{"date-parts":[[2020,4,1]],"date-time":"2020-04-01T19:02:58Z","timestamp":1585767778000},"page":"209-222","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Species-Based Differential Evolution with Migration for Multimodal Optimization"],"prefix":"10.1007","author":[{"given":"Wei","family":"Li","sequence":"first","affiliation":[]},{"given":"Yaochi","family":"Fan","sequence":"additional","affiliation":[]},{"given":"Qiaoyong","family":"Jiang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,4,2]]},"reference":[{"issue":"3","key":"17_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TMAG.2017.2749506","volume":"54","author":"CH Yoo","year":"2018","unstructured":"Yoo, C.H.: A new multi-modal optimization approach and its application to the design of electric machines. IEEE Trans. Magn. 54(3), 1\u20134 (2018)","journal-title":"IEEE Trans. Magn."},{"doi-asserted-by":"publisher","unstructured":"Tanabe, R., Ishibuchi., H.: A review of evolutionary multi-modal multi-objective optimization. IEEE Trans. Evol. Comput., 1\u20139 (2019). https:\/\/doi.org\/10.1109\/TEVC.2019.2909744","key":"17_CR2","DOI":"10.1109\/TEVC.2019.2909744"},{"issue":"9","key":"17_CR3","doi-asserted-by":"publisher","first-page":"3507","DOI":"10.1109\/TCYB.2018.2846179","volume":"49","author":"XG Peng","year":"2019","unstructured":"Peng, X.G., Jin, Y.C., Wang, H.: Multimodal optimization enhanced cooperative co-evolution for large-scale optimization. IEEE Trans. Cybern. 49(9), 3507\u20133520 (2019)","journal-title":"IEEE Trans. Cybern."},{"key":"17_CR4","doi-asserted-by":"publisher","first-page":"271","DOI":"10.1007\/s00521-016-2686-9","volume":"30","author":"A Naik","year":"2016","unstructured":"Naik, A., Satapathy, S.C., Ashour, A.S., Dey, N.: Social group optimization for global optimization of multimodal functions and data clustering problems. Neural Comput. Appl. 30, 271\u2013287 (2016). https:\/\/doi.org\/10.1007\/s00521-016-2686-9","journal-title":"Neural Comput. Appl."},{"issue":"5","key":"17_CR5","doi-asserted-by":"publisher","first-page":"2128","DOI":"10.1109\/TPWRD.2015.2410172","volume":"30","author":"A Yazdanpanah","year":"2015","unstructured":"Yazdanpanah, A., Singh, R., Gole, A., Filizadeh, S., Muller, J.C., Jayasinghe, R.P.: A parallel multi-modal optimization algorithm for simulation-based design of power systems. IEEE Trans. Power Delivery 30(5), 2128\u20132137 (2015)","journal-title":"IEEE Trans. Power Delivery"},{"unstructured":"Thomsen, R.: Multimodal optimization using crowding-based differential evolution. In: IEEE Congress on Evolutionary Computation, 19\u201323 June, Portland, OR, USA, pp. 1382\u20131389 (2004)","key":"17_CR6"},{"issue":"3","key":"17_CR7","doi-asserted-by":"publisher","first-page":"207","DOI":"10.1162\/106365602760234081","volume":"10","author":"J-P Li","year":"2002","unstructured":"Li, J.-P., Balazs, M.E., Parks, G.T., Clarkson, P.J.: A species conserving genetic algorithm for multimodal function optimization. Evol. Comput. 10(3), 207\u2013234 (2002)","journal-title":"Evol. Comput."},{"issue":"6","key":"17_CR8","doi-asserted-by":"publisher","first-page":"1200","DOI":"10.1109\/TNNLS.2014.2298402","volume":"25","author":"W Dong","year":"2014","unstructured":"Dong, W., Zhou, M.: Gaussian classifier-based evolutionary strategy for multimodal opti-mization. IEEE Trans. Neural Netw. Learn. Syst. 25(6), 1200\u20131216 (2014)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"doi-asserted-by":"crossref","unstructured":"Petrowski, A.: A clearing procedure as a niching method for genetic algorithms. In: IEEE Congress on Evolutionary Computation, 20\u201322 May, Nagoya, Japan, pp. 798\u2013803 (1996)","key":"17_CR9","DOI":"10.1109\/ICEC.1996.542703"},{"unstructured":"Goldberg, D.-E., Richardson, J.: Genetic algorithms with sharing for multimodal function optimization. In: International Conference on Genetic Algorithms, pp. 41\u201349 (1987)","key":"17_CR10"},{"issue":"4","key":"17_CR11","doi-asserted-by":"publisher","first-page":"341","DOI":"10.1023\/A:1008202821328","volume":"11","author":"R Storn","year":"1997","unstructured":"Storn, R., Price, K.V.: Differential evolution\u2013a simple and efficient heuristic for global optimization over continuous spaces. J. Global Optim. 11(4), 341\u2013359 (1997). https:\/\/doi.org\/10.1023\/A:1008202821328","journal-title":"J. Global Optim."},{"issue":"1","key":"17_CR12","doi-asserted-by":"publisher","first-page":"150","DOI":"10.1109\/TEVC.2009.2026270","volume":"14","author":"X Li","year":"2010","unstructured":"Li, X.: Niching without niching parameters: particle swarm optimization using a ring topology. IEEE Trans. Evol. Comput. 14(1), 150\u2013169 (2010)","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"2","key":"17_CR13","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1109\/TEVC.2016.2591064","volume":"21","author":"Q Yang","year":"2017","unstructured":"Yang, Q., Chen, W.-N., Yu, Z., Li, Y., Zhang, H., Zhang, J.: Adaptive multimodal continuous ant colony optimization. IEEE Trans. Evol. Comput. 21(2), 191\u2013205 (2017)","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"2","key":"17_CR14","doi-asserted-by":"publisher","first-page":"246","DOI":"10.1109\/TEVC.2014.2313659","volume":"19","author":"S Biswas","year":"2015","unstructured":"Biswas, S., Kundu, S., Das, S.: Inducing niching behavior in differential evolution through local information sharing. IEEE Trans. Evol. Comput. 19(2), 246\u2013263 (2015)","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"1","key":"17_CR15","doi-asserted-by":"publisher","first-page":"64","DOI":"10.1109\/TCYB.2015.2394466","volume":"46","author":"S Hui","year":"2016","unstructured":"Hui, S., Suganthan, P.-N.: Ensemble and arithmetic recombination based speciation differen-tial evolution for multimodal optimization. IEEE Trans. Cybern. 46(1), 64\u201374 (2016)","journal-title":"IEEE Trans. Cybern."},{"issue":"10","key":"17_CR16","doi-asserted-by":"publisher","first-page":"1726","DOI":"10.1109\/TCYB.2013.2292971","volume":"44","author":"S Biswas","year":"2014","unstructured":"Biswas, S., Kundu, S., Das, S.: An improved parent-centric mutation with normalized neighborhoods for inducing niching behavior in differential evolution. IEEE Trans. Cybern. 44(10), 1726\u20131737 (2014)","journal-title":"IEEE Trans. Cybern."},{"doi-asserted-by":"crossref","unstructured":"Li, X.: Efficient differential evolution using speciation for multimodal function optimization. In: Conference on Genetic & Evolutionary Computation, pp. 873\u2013880. ACM (2005)","key":"17_CR17","DOI":"10.1145\/1068009.1068156"},{"key":"17_CR18","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"105","DOI":"10.1007\/978-3-540-24854-5_10","volume-title":"Genetic and Evolutionary Computation \u2013 GECCO 2004","author":"X Li","year":"2004","unstructured":"Li, X.: Adaptively choosing neighbourhood bests using species in a particle swarm optimizer for multimodal function optimization. In: Deb, K. (ed.) GECCO 2004. LNCS, vol. 3102, pp. 105\u2013116. Springer, Heidelberg (2004). https:\/\/doi.org\/10.1007\/978-3-540-24854-5_10"},{"issue":"1","key":"17_CR19","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1162\/106365603321829023","volume":"11","author":"JP Li","year":"2003","unstructured":"Li, J.P., Balazs, M.E., Parks, G.T., Clarkson, P.-J.: Erratum: a species conserving genetic algorithm for multimodal function optimization. Evol. Comput. 11(1), 107\u2013109 (2003)","journal-title":"Evol. Comput."},{"unstructured":"Li, X., Engelbrecht, A., Epitropakis, M.: Benchmark functions for CEC 2013 special session and competition on niching methods for multimodal function optimization. Technical Report, Royal Melbourne Institute of Technology (2013)","key":"17_CR20"},{"doi-asserted-by":"crossref","unstructured":"Li, X.: A multimodal particle swarm optimizer based on fitness Euclidean-distance ratio. In: Genetic and Evolutionary Computation Conference (GECCO 2007), 7\u201311 July, pp. 78\u201385. ACM, London (2007)","key":"17_CR21","DOI":"10.1145\/1276958.1276970"},{"issue":"5","key":"17_CR22","doi-asserted-by":"publisher","first-page":"601","DOI":"10.1109\/TEVC.2011.2161873","volume":"16","author":"BY Qu","year":"2012","unstructured":"Qu, B.Y., Suganthan, P.N., Liang, J.J.: Differential evolution with neighborhood mutation for multimodal optimization. IEEE Trans. Evol. Comput. 16(5), 601\u2013614 (2012)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"17_CR23","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1109\/TEVC.2010.2087271","volume":"15","author":"Y Wang","year":"2011","unstructured":"Wang, Y., Cai, Z.X., Zhang, Q.F.: Differential evolution with composite trial vector generation strategies and control parameters. IEEE Trans. Evol. Comput. 15, 55\u201366 (2011)","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"3","key":"17_CR24","doi-asserted-by":"publisher","first-page":"307","DOI":"10.1007\/s00500-008-0323-y","volume":"13","author":"J Alcal-Fdez","year":"2009","unstructured":"Alcal-Fdez, J., et al.: KEEL: a software tool to as-sess evolutionary algorithms to data mining problems. Soft. Comput. 13(3), 307\u2013318 (2009)","journal-title":"Soft. Comput."}],"container-title":["Communications in Computer and Information Science","Bio-inspired Computing: Theories and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-15-3425-6_17","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,29]],"date-time":"2023-09-29T11:31:51Z","timestamp":1695987111000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-981-15-3425-6_17"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9789811534249","9789811534256"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-981-15-3425-6_17","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"2 April 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"BIC-TA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Bio-Inspired Computing: Theories and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Zhengzhou","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 November 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 November 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"bicta2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/2019.bicta.org","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":"197","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":"121","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":"61% - 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":"3","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":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}