{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T00:40:46Z","timestamp":1742949646247,"version":"3.40.3"},"publisher-location":"Cham","reference-count":34,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031366215"},{"type":"electronic","value":"9783031366222"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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":[[2023]]},"DOI":"10.1007\/978-3-031-36622-2_13","type":"book-chapter","created":{"date-parts":[[2023,7,7]],"date-time":"2023-07-07T12:02:36Z","timestamp":1688731356000},"page":"158-167","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Particle Swarm Optimizer Without Communications Among Particles"],"prefix":"10.1007","author":[{"given":"JunQi","family":"Zhang","sequence":"first","affiliation":[]},{"given":"XuRui","family":"Huang","sequence":"additional","affiliation":[]},{"given":"Huan","family":"Liu","sequence":"additional","affiliation":[]},{"given":"MengChu","family":"Zhou","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,7,8]]},"reference":[{"issue":"5","key":"13_CR1","doi-asserted-by":"publisher","first-page":"2459","DOI":"10.1109\/TAC.2021.3077457","volume":"67","author":"S Al-Abri","year":"2022","unstructured":"Al-Abri, S., Zhang, F.: A distributed active perception strategy for source seeking and level curve tracking. IEEE Trans. Autom. Control 67(5), 2459\u20132465 (2022)","journal-title":"IEEE Trans. Autom. Control"},{"key":"13_CR2","unstructured":"Awad, N., Ali, M., Liang, J., Qu, B., Suganthan, P.: Problem definitions and evaluation criteria for the CEC 2017 special session and competition on single objective real-parameter numerical optimization. Nanyang Technological University, Singapore and Computational Intelligence Laboratory, Zhengzhou University, Zhengzhou, China, Technical report 10 (2017)"},{"issue":"9","key":"13_CR3","doi-asserted-by":"publisher","first-page":"2308","DOI":"10.1109\/TAC.2012.2186927","volume":"57","author":"SI Azuma","year":"2012","unstructured":"Azuma, S.I., Sakar, M.S., Pappas, G.J.: Stochastic source seeking by mobile robots. IEEE Trans. Autom. Control 57(9), 2308\u20132321 (2012)","journal-title":"IEEE Trans. Autom. Control"},{"issue":"4","key":"13_CR4","doi-asserted-by":"publisher","first-page":"689","DOI":"10.1109\/TEVC.2018.2880894","volume":"23","author":"T Blackwell","year":"2019","unstructured":"Blackwell, T., Kennedy, J.: Impact of communication topology in particle swarm optimization. IEEE Trans. Evol. Comput. 23(4), 689\u2013702 (2019)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"13_CR5","doi-asserted-by":"crossref","unstructured":"Bratton, D., Kennedy, J.: Defining a standard for particle swarm optimization. In: IEEE Swarm Intelligence Symposium, pp. 120\u2013127 (2007)","DOI":"10.1109\/SIS.2007.368035"},{"issue":"1","key":"13_CR6","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1007\/s13748-011-0005-3","volume":"1","author":"J Ceberio","year":"2012","unstructured":"Ceberio, J., Irurozki, E., Mendiburu, A., Lozano, J.A.: A review on estimation of distribution algorithms in permutation-based combinatorial optimization problems. Progr. Artif. Intell. 1(1), 103\u2013117 (2012)","journal-title":"Progr. Artif. Intell."},{"issue":"1","key":"13_CR7","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1109\/4235.985692","volume":"6","author":"M Clerc","year":"2002","unstructured":"Clerc, M., Kennedy, J.: The particle swarm-explosion, stability, and convergence in a multidimensional complex space. IEEE Trans. Evol. Comput. 6(1), 58\u201373 (2002)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"13_CR8","unstructured":"Colorni, A., Dorigo, M., Maniezzo, V., et al.: Distributed optimization by ant colonies. In: Proceedings of the First European Conference on Artificial Life, vol. 142, pp. 134\u2013142 (1991)"},{"key":"13_CR9","doi-asserted-by":"crossref","unstructured":"Eberhart, R.C., Kennedy, J.: A new optimizer using particle swarm theory. In: Proceedings of the Sixth International Symposium on Micro Machine and Human Science, vol. 1, pp. 39\u201343 (1995)","DOI":"10.1109\/MHS.1995.494215"},{"issue":"2","key":"13_CR10","doi-asserted-by":"publisher","first-page":"288","DOI":"10.1109\/TSMCA.2007.914796","volume":"38","author":"SY Ho","year":"2008","unstructured":"Ho, S.Y., Lin, H.S., Liauh, W.H., Ho, S.J.: OPSO: orthogonal particle swarm optimization and its application to task assignment problems. IEEE Trans. Syst. Man Cybern. Part A Syst. Hum. 38(2), 288\u2013298 (2008)","journal-title":"IEEE Trans. Syst. Man Cybern. Part A Syst. Hum."},{"key":"13_CR11","doi-asserted-by":"crossref","unstructured":"Keles, C., Alagoz, B.B., Kaygusuz, A.: Multi-source energy mixing for renewable energy microgrids by particle swarm optimization. In: International Artificial Intelligence and Data Processing Symposium, pp. 1\u20135 (2017)","DOI":"10.1109\/IDAP.2017.8090163"},{"key":"13_CR12","doi-asserted-by":"crossref","unstructured":"Kennedy, J., Eberhart, R., et al.: Particle swarm optimization. In: Proceedings of IEEE International Conference on Neural Networks, vol. 4, pp. 1942\u20131948 (1995)","DOI":"10.1109\/ICNN.1995.488968"},{"issue":"3","key":"13_CR13","doi-asserted-by":"publisher","first-page":"496","DOI":"10.1109\/JAS.2021.1004356","volume":"9","author":"RA Khalil","year":"2022","unstructured":"Khalil, R.A., Saeed, N., Babar, M.I., Jan, T., Din, S.: Bayesian multidimensional scaling for location awareness in hybrid-internet of underwater things. IEEE\/CAA J. Autom. Sinica 9(3), 496\u2013509 (2022)","journal-title":"IEEE\/CAA J. Autom. Sinica"},{"key":"13_CR14","doi-asserted-by":"crossref","unstructured":"Kinsey, J.C.R., Eustice, M., Whitcomb, L.: A survey of underwater vehicle navigation: Recent advances and new challenges. In: Proceedings of the IFAC Conference on Manoeuvering Control Marine Craft, vol. 88, pp. 1\u201312 (2006)","DOI":"10.1109\/OCEANS.2006.306931"},{"key":"13_CR15","doi-asserted-by":"crossref","unstructured":"Robinson, J., Sinton, S., Rahmat-Samii, Y.: Particle swarm, genetic algorithm, and their hybrids: optimization of a profiled corrugated horn antenna. In: IEEE Antennas and Propagation Society International Symposium, vol. 1, pp. 314\u2013317 (2002)","DOI":"10.1109\/APS.2002.1016311"},{"key":"13_CR16","unstructured":"Shi, Y., Eberhart, R.: A modified particle swarm optimizer. In: Proceedings of IEEE World Congress on Computational Intelligence, pp. 69\u201373 (1998)"},{"issue":"3","key":"13_CR17","doi-asserted-by":"publisher","first-page":"289","DOI":"10.1109\/TEVC.2004.826068","volume":"8","author":"MP Wachowiak","year":"2004","unstructured":"Wachowiak, M.P., Smol\u00edkov\u00e1, R., Zheng, Y., Zurada, J.M., Elmaghraby, A.S.: An approach to multimodal biomedical image registration utilizing particle swarm optimization. IEEE Trans. Evol. Comput. 8(3), 289\u2013301 (2004)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"13_CR18","doi-asserted-by":"crossref","unstructured":"Wang, J., Liu, C., Zhou, M.: Improved bacterial foraging algorithm for cell formation and product scheduling considering learning and forgetting factors in cellular manufacturing systems. IEEE Syst. J. 14(2), 3047\u20133056 (2020)","DOI":"10.1109\/JSYST.2019.2963222"},{"key":"13_CR19","doi-asserted-by":"publisher","unstructured":"Wang, X., Xing, K., Yan, C., Zhou, M.: A novel MOEA\/D for multi-objective scheduling of flexible manufacturing systems. Complexity 2019 Article ID 5734149, 14 p (2019) https:\/\/doi.org\/10.1155\/2019\/5734149","DOI":"10.1155\/2019\/5734149"},{"key":"13_CR20","doi-asserted-by":"crossref","unstructured":"Wang, Y., Gao, S., Zhou, M., Yu, Y.: A multi-layered gravitational search algorithm for function optimization and real-world problems. IEEE\/CAA J. Autom. Sin. 8(1), 94\u2013109 (2021)","DOI":"10.1109\/JAS.2020.1003462"},{"key":"13_CR21","doi-asserted-by":"publisher","unstructured":"Wang, Z., Gao, S., Zhou, M., Sato, S., Cheng, J., Wang, J.: Information-theory-based nondominated sorting ant colony optimization for multiobjective feature selection in classification, IEEE Trans. Cybern. (2022). https:\/\/doi.org\/10.1109\/TCYB.2022.3185554","DOI":"10.1109\/TCYB.2022.3185554"},{"key":"13_CR22","doi-asserted-by":"crossref","unstructured":"Wu, Q., Zhou, M., Zhu, Q., Xia, Y., Wen, J.: MOELS: multiobjective evolutionary list scheduling for cloud workflows. IEEE Trans. Autom. Sci. Eng. 17(1), 166\u2013176 (2020)","DOI":"10.1109\/TASE.2019.2918691"},{"key":"13_CR23","doi-asserted-by":"publisher","unstructured":"Yu, Y., et al.: Scale-free network-based differential evolution to solve function optimization and parameter estimation of photovoltaic models. Swarm Evol. Comput. 74, 101142 (2022). https:\/\/doi.org\/10.1016\/j.swevo.2022.101142","DOI":"10.1016\/j.swevo.2022.101142"},{"key":"13_CR24","doi-asserted-by":"crossref","unstructured":"Zhang, J., Lu, Y., Che, L., Zhou, M.: Moving-distance-minimized PSO for mobile robot swarm, IEEE Trans. Cybern. 52(9), 9871\u20139881 (2022)","DOI":"10.1109\/TCYB.2021.3079346"},{"key":"13_CR25","doi-asserted-by":"crossref","unstructured":"Zhang, J., et al:. PSO-based sparse source location in large-scale environments with a uav swarm, IEEE Trans. Intell. Transp. Syst. 24(5), 5249\u20135258 (2023)","DOI":"10.1109\/TITS.2023.3237570"},{"key":"13_CR26","doi-asserted-by":"crossref","unstructured":"Zhang, J., Zhu, X., Wang, Y., Zhou, M.: Dual-environmental particle swarm optimizer in noisy and noise-free environments. IEEE Trans. Cybern. 49(6), 2011\u20132021 (2019)","DOI":"10.1109\/TCYB.2018.2817020"},{"key":"13_CR27","doi-asserted-by":"crossref","unstructured":"Zhang, P., Zhou, M., Wang, X.: An intelligent optimization method for optimal virtual machine allocation in cloud data centers, IEEE Trans. Autom. Sci. Eng. 17(4), 1725\u20131735 (2020)","DOI":"10.1109\/TASE.2020.2975225"},{"key":"13_CR28","doi-asserted-by":"crossref","unstructured":"Zhao, J., Liu, S.X., Zhou, M., Guo, X.W., Qi, L.: Modified cuckoo search algorithm to solve economic power dispatch optimization problems. IEEE\/CAA J. Autom. Sin. 5(4), 794\u2013806 (2018)","DOI":"10.1109\/JAS.2018.7511138"},{"key":"13_CR29","doi-asserted-by":"crossref","unstructured":"Zhao, Z., Zhou M., Liu, S.: Iterated greedy algorithms for flow-shop scheduling problems: a tutorial. IEEE Trans. Autom. Sci. Eng. 19(1) 251\u2013261 (2022)","DOI":"10.1109\/TASE.2020.3027532"},{"key":"13_CR30","doi-asserted-by":"publisher","unstructured":"Zhou, J., Wu, Q., Zhou, M., Wen, J., Al-Turki, Y., Abusorrah, A.: LAGAM: a length-adaptive genetic algorithm with markov blanket for high-dimensional feature selection in classification, IEEE Trans. Cybern. (2022) https:\/\/doi.org\/10.1109\/TCYB.2022.3163577","DOI":"10.1109\/TCYB.2022.3163577"},{"key":"13_CR31","doi-asserted-by":"crossref","unstructured":"Zhou, Y., Xu, W., Fu, Z.-H., Zhou, M.: Multi-neighborhood simulated annealing-based iterated local search for colored traveling salesman problems. IEEE Trans. on Intell. Transp. Syst. 23(9), 16072\u201316082 (2022)","DOI":"10.1109\/TITS.2022.3147924"},{"key":"13_CR32","doi-asserted-by":"crossref","unstructured":"Zhu, H., Liu, G., Zhou, M., Xie, Y., Kang, Q.: Dandelion algorithm with probability-based mutation. IEEE Access 7, 97974\u201397985 (2019)","DOI":"10.1109\/ACCESS.2019.2927846"},{"key":"13_CR33","doi-asserted-by":"crossref","unstructured":"Zhu, X., Li, J., Zhou, M.: Target coverage-oriented deployment of rechargeable directional sensor networks with a mobile charger. IEEE Internet Things J. 6(3), 5196\u20135208 (2019)","DOI":"10.1109\/JIOT.2019.2899155"},{"key":"13_CR34","doi-asserted-by":"crossref","unstructured":"Zuo, X., et al.: Optimizing hospital emergency department layout via multiobjective tabu search. IEEE Trans. Autom. Sci. Eng. 16(3), 1137\u20131147 (2019)","DOI":"10.1109\/TASE.2018.2873098"}],"container-title":["Lecture Notes in Computer Science","Advances in Swarm Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-36622-2_13","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,23]],"date-time":"2024-10-23T20:18:53Z","timestamp":1729714733000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-36622-2_13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031366215","9783031366222"],"references-count":34,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-36622-2_13","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"8 July 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICSI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Swarm Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Shenzhen","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":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 July 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 July 2023","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":"swarm2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-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":"170","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":"81","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":"48% - 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":"2.6","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":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}