{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T21:03:48Z","timestamp":1742936628275,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":28,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819615346"},{"type":"electronic","value":"9789819615353"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-981-96-1535-3_25","type":"book-chapter","created":{"date-parts":[[2025,2,13]],"date-time":"2025-02-13T12:25:00Z","timestamp":1739449500000},"page":"242-255","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Dimensional Difference-Based Population Size Adjustment Framework for Gannet Optimization Algorithm"],"prefix":"10.1007","author":[{"given":"Jeng-Shyang","family":"Pan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kunpeng","family":"Han","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shu-Chuan","family":"Chu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhi","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Li","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,2,14]]},"reference":[{"key":"25_CR1","unstructured":"Yang, X.S.: Nature-Inspired Metaheuristic Algorithms. Luniver Press (2010)"},{"issue":"10","key":"25_CR2","doi-asserted-by":"publisher","first-page":"1627","DOI":"10.1109\/JAS.2021.1004129","volume":"8","author":"J Tang","year":"2021","unstructured":"Tang, J., Liu, G., Pan, Q.: A review on representative swarm intelligence algorithms for solving optimization problems: applications and trends. IEEE\/CAA J. Automatica Sinica 8(10), 1627\u20131643 (2021)","journal-title":"IEEE\/CAA J. Automatica Sinica"},{"key":"25_CR3","unstructured":"Mitchell, M.: An Introduction to Genetic Algorithms. MIT Press (1998)"},{"key":"25_CR4","doi-asserted-by":"crossref","unstructured":"Price, K.V.: Differential evolution. In: Handbook of Optimization: From Classical to Modern Approach, pp. 187\u2013214. Springer, Heidelberg (2013)","DOI":"10.1007\/978-3-642-30504-7_8"},{"key":"25_CR5","doi-asserted-by":"crossref","unstructured":"Kennedy, J., Eberhart, R.: Particle swarm optimization. In: Proceedings of ICNN 1995-International Conference on Neural Networks, vol. 4, pp. 1942\u20131948. IEEE (1995)","DOI":"10.1109\/ICNN.1995.488968"},{"issue":"4","key":"25_CR6","doi-asserted-by":"publisher","first-page":"28","DOI":"10.1109\/MCI.2006.329691","volume":"1","author":"M Dorigo","year":"2006","unstructured":"Dorigo, M., Birattari, M., Stutzle, T.: Ant colony optimization. IEEE Comput. Intell. Mag. 1(4), 28\u201339 (2006)","journal-title":"IEEE Comput. Intell. Mag."},{"issue":"1","key":"25_CR7","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1214\/ss\/1177011077","volume":"8","author":"D Bertsimas","year":"1993","unstructured":"Bertsimas, D., Tsitsiklis, J.: Simulated annealing. Stat. Sci. 8(1), 10\u201315 (1993)","journal-title":"Stat. Sci."},{"issue":"1","key":"25_CR8","first-page":"108","volume":"214","author":"D Karaboga","year":"2009","unstructured":"Karaboga, D., Akay, B.: A comparative study of artificial bee colony algorithm. Appl. Math. Comput. 214(1), 108\u2013132 (2009)","journal-title":"Appl. Math. Comput."},{"issue":"2","key":"25_CR9","first-page":"1","volume":"14","author":"DT Pham","year":"2023","unstructured":"Pham, D.T., Hoang, D.T.T., Nguyen, T.T., et al.: An improved whale optimization algorithm for optimal multi-threshold image segmentation. J. Inf. Hiding Multim. Signal Process. 14(2), 1\u201311 (2023)","journal-title":"J. Inf. Hiding Multim. Signal Process."},{"key":"25_CR10","doi-asserted-by":"crossref","unstructured":"Yuan, X., Pan, J.S., Chu, S.C., et al.: Binary tumbleweed algorithm for application of feature selection. In: International Conference on Intelligent Information Hiding and Multimedia Signal Processing, pp. 13\u201320. Springer, Singapore (2022)","DOI":"10.1007\/978-981-99-0605-5_2"},{"issue":"1","key":"25_CR11","first-page":"59","volume":"7","author":"X Xu","year":"2022","unstructured":"Xu, X., Cui, J., Chen, X., et al.: A facial expression recognition method based on residual separable convolutional neural network. J. Netw. Intell. 7(1), 59\u201369 (2022)","journal-title":"J. Netw. Intell."},{"key":"25_CR12","doi-asserted-by":"crossref","unstructured":"Yang, X.S.: Engineering Optimization: An Introduction with Metaheuristic Applications. Wiley (2010)","DOI":"10.1002\/9780470640425"},{"key":"25_CR13","unstructured":"Gan, D.S.H.Y., Bevilacqua, V., Figueroa, J.C.: Advanced Intelligent Computing (2005)"},{"key":"25_CR14","doi-asserted-by":"crossref","unstructured":"Acharya, T., Ray, A.K.: Image Processing: Principles and Applications. Wiley (2005)","DOI":"10.1002\/0471745790"},{"key":"25_CR15","doi-asserted-by":"publisher","first-page":"343","DOI":"10.1016\/j.matcom.2022.06.007","volume":"202","author":"JS Pan","year":"2022","unstructured":"Pan, J.S., Zhang, L.G., Wang, R.B., et al.: Gannet optimization algorithm: a new metaheuristic algorithm for solving engineering optimization problems. Math. Comput. Simul. 202, 343\u2013373 (2022)","journal-title":"Math. Comput. Simul."},{"key":"25_CR16","doi-asserted-by":"crossref","unstructured":"Shlesinger, M.F., Zaslavsky, G.M., Frisch, U.: L\u00e9vy flights and related topics in physics (1995)","DOI":"10.1007\/3-540-59222-9"},{"key":"25_CR17","doi-asserted-by":"crossref","unstructured":"Sudholt, D.: Parallel evolutionary algorithms. Springer Handbook of Computational Intelligence, pp. 929\u2013959 (2015)","DOI":"10.1007\/978-3-662-43505-2_46"},{"key":"25_CR18","first-page":"114","volume":"7","author":"ZB Pan","year":"2022","unstructured":"Pan, Z.B., Yang, L., Xu, Z.X., et al.: A NEC-based parallel differential evolution algorithm with MKL\/CUDA. J. Netw. Intell 7, 114\u2013128 (2022)","journal-title":"J. Netw. Intell"},{"issue":"2","key":"25_CR19","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1016\/j.swevo.2011.05.001","volume":"1","author":"Y Jin","year":"2011","unstructured":"Jin, Y.: Surrogate-assisted evolutionary computation: recent advances and future challenges. Swarm Evol. Comput. 1(2), 61\u201370 (2011)","journal-title":"Swarm Evol. Comput."},{"key":"25_CR20","doi-asserted-by":"publisher","first-page":"96","DOI":"10.1016\/j.ins.2013.03.026","volume":"239","author":"F Neri","year":"2013","unstructured":"Neri, F., Mininno, E., Iacca, G.: Compact particle swarm optimization. Inf. Sci. 239, 96\u2013121 (2013)","journal-title":"Inf. Sci."},{"issue":"2","key":"25_CR21","doi-asserted-by":"publisher","first-page":"350","DOI":"10.4304\/jsw.9.2.350-357","volume":"9","author":"X Xia","year":"2014","unstructured":"Xia, X., Liu, J., Li, Y.: Particle swarm optimization algorithm with reverse-learning and local-learning behavior. J. Softw. 9(2), 350\u2013357 (2014)","journal-title":"J. Softw."},{"issue":"2","key":"25_CR22","doi-asserted-by":"publisher","first-page":"1373","DOI":"10.1007\/s10462-019-09704-9","volume":"53","author":"E Varol Altay","year":"2020","unstructured":"Varol Altay, E., Alatas, B.: Bird swarm algorithms with chaotic mapping. Artif. Intell. Rev. 53(2), 1373\u20131414 (2020)","journal-title":"Artif. Intell. Rev."},{"issue":"2","key":"25_CR23","doi-asserted-by":"publisher","first-page":"439","DOI":"10.3390\/math11020439","volume":"11","author":"JS Pan","year":"2023","unstructured":"Pan, J.S., Sun, B., Chu, S.C., et al.: A parallel compact gannet optimization algorithm for solving engineering optimization problems. Mathematics 11(2), 439 (2023)","journal-title":"Mathematics"},{"key":"25_CR24","doi-asserted-by":"crossref","unstructured":"Ting, T.O., Yang, X.S., Cheng, S., et al.: Hybrid metaheuristic algorithms: past, present, and future. Recent Adv. Swarm Intell. Evolution. Comput. 71\u201383 (2015)","DOI":"10.1007\/978-3-319-13826-8_4"},{"key":"25_CR25","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2024.120110","volume":"660","author":"Y Qin","year":"2024","unstructured":"Qin, Y., Deng, L., Li, C., et al.: A dimensional difference-based population size adjustment framework for differential evolution. Inf. Sci. 660, 120110 (2024)","journal-title":"Inf. Sci."},{"key":"25_CR26","doi-asserted-by":"publisher","first-page":"164","DOI":"10.1016\/j.ins.2012.09.019","volume":"223","author":"W Zhu","year":"2013","unstructured":"Zhu, W., Tang, Y., Fang, J., et al.: Adaptive population tuning scheme for differential evolution. Inf. Sci. 223, 164\u2013191 (2013)","journal-title":"Inf. Sci."},{"key":"25_CR27","doi-asserted-by":"publisher","first-page":"353","DOI":"10.1016\/j.ins.2022.07.075","volume":"609","author":"Z Zeng","year":"2022","unstructured":"Zeng, Z., Hong, Z., Zhang, H., et al.: Improving differential evolution using a best discarded vector selection strategy. Inf. Sci. 609, 353\u2013375 (2022)","journal-title":"Inf. Sci."},{"key":"25_CR28","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1016\/j.ins.2023.01.120","volume":"629","author":"C Li","year":"2023","unstructured":"Li, C., Sun, G., Deng, L., et al.: A population state evaluation-based improvement framework for differential evolution. Inf. Sci. 629, 15\u201338 (2023)","journal-title":"Inf. Sci."}],"container-title":["Lecture Notes in Electrical Engineering","Genetic and Evolutionary Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-96-1535-3_25","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,13]],"date-time":"2025-02-13T12:25:12Z","timestamp":1739449512000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-96-1535-3_25"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9789819615346","9789819615353"],"references-count":28,"URL":"https:\/\/doi.org\/10.1007\/978-981-96-1535-3_25","relation":{},"ISSN":["1876-1100","1876-1119"],"issn-type":[{"type":"print","value":"1876-1100"},{"type":"electronic","value":"1876-1119"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"14 February 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICGEC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Genetic and Evolutionary Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Miyazaki","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Japan","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 August 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 August 2024","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":"icgec2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/icgec24.github.io\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}