{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T18:06:36Z","timestamp":1743012396931,"version":"3.40.3"},"publisher-location":"Cham","reference-count":18,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030603755"},{"type":"electronic","value":"9783030603762"}],"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\/978-3-030-60376-2_8","type":"book-chapter","created":{"date-parts":[[2020,10,22]],"date-time":"2020-10-22T12:02:22Z","timestamp":1603368142000},"page":"96-106","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Control Parameter Importance and Sensitivity Analysis of the Multi-Guide Particle Swarm Optimization Algorithm"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8508-1617","authenticated-orcid":false,"given":"Timothy G.","family":"Carolus","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0242-3539","authenticated-orcid":false,"given":"Andries P.","family":"Engelbrecht","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,10,23]]},"reference":[{"key":"8_CR1","unstructured":"Beielstein, T., Parsopoulos, K.E., Vrahatis, M.N.: Tuning PSO parameters through sensitivity analysis. Universit\u00e4tsbibliothek Dortmund (2002)"},{"issue":"8","key":"8_CR2","doi-asserted-by":"publisher","first-page":"937","DOI":"10.1016\/j.ins.2005.02.003","volume":"176","author":"F Van den Bergh","year":"2006","unstructured":"Van den Bergh, F., Engelbrecht, A.P.: A study of particle swarm optimization particle trajectories. Inf. Sci. 176(8), 937\u2013971 (2006)","journal-title":"Inf. Sci."},{"issue":"3","key":"8_CR3","first-page":"378","volume":"21","author":"MR Bonyadi","year":"2016","unstructured":"Bonyadi, M.R., Michalewicz, Z.: Impacts of coefficients on movement patterns in the particle swarm optimization algorithm. IEEE Trans. Evol. Computat. 21(3), 378\u2013390 (2016)","journal-title":"IEEE Trans. Evol. Computat."},{"key":"8_CR4","doi-asserted-by":"crossref","unstructured":"Bratton, D., Kennedy, J.: Defining a standard for particle swarm optimization. In: 2007 IEEE Swarm Intelligence Symposium, pp. 120\u2013127. IEEE (2007)","DOI":"10.1109\/SIS.2007.368035"},{"issue":"1","key":"8_CR5","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman, L.: Random forests. Machine Learn. 45(1), 5\u201332 (2001)","journal-title":"Machine Learn."},{"issue":"1","key":"8_CR6","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s11721-017-0141-x","volume":"12","author":"CW Cleghorn","year":"2017","unstructured":"Cleghorn, C.W., Engelbrecht, A.P.: Particle swarm stability: a theoretical extension using the non-stagnate distribution assumption. Swarm Intell. 12(1), 1\u201322 (2017). https:\/\/doi.org\/10.1007\/s11721-017-0141-x","journal-title":"Swarm Intell."},{"key":"8_CR7","unstructured":"Fonseca, C.M., Paquete, L., L\u00f3pez-Ib\u00e1nez, M.: An improved dimension-sweep algorithm for the hypervolume indicator. In: 2006 IEEE International Conference on Evolutionary Computation, pp. 1157\u20131163. IEEE (2006)"},{"key":"8_CR8","unstructured":"Hoos, H., Leyton-Brown, K., Hutter, F.: An efficient approach for assessing hyperparameter importance. In: International Conference on Machine Learning, pp. 754\u2013762 (2014)"},{"issue":"5","key":"8_CR9","doi-asserted-by":"publisher","first-page":"477","DOI":"10.1109\/TEVC.2005.861417","volume":"10","author":"S Huband","year":"2006","unstructured":"Huband, S., Hingston, P., Barone, L., While, L.: A review of multiobjective test problems and a scalable test problem toolkit. IEEE Trans. Evol. Computat. 10(5), 477\u2013506 (2006)","journal-title":"IEEE Trans. Evol. Computat."},{"issue":"1","key":"8_CR10","doi-asserted-by":"publisher","first-page":"8","DOI":"10.1016\/j.ipl.2006.10.005","volume":"102","author":"M Jiang","year":"2007","unstructured":"Jiang, M., Luo, Y., Yang, S.: Stochastic convergence analysis and parameter selection of the standard particle swarm optimization algorithm. Inf. Process. Lett. 102(1), 8\u201316 (2007)","journal-title":"Inf. Process. Lett."},{"key":"8_CR11","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"},{"key":"8_CR12","doi-asserted-by":"crossref","unstructured":"Raquel, C.R., Naval Jr, P.C.: An effective use of crowding distance in multiobjective particle swarm optimization. In: Proceedings of the 7th Annual Conference on Genetic and Evolutionary Computation, pp. 257\u2013264 (2005)","DOI":"10.1145\/1068009.1068047"},{"key":"8_CR13","unstructured":"Scheepers, C.: Multi-guided particle swarm optimization: A multi-objective particle swarm optimizer, unpublished thesis (2017)"},{"issue":"3","key":"8_CR14","doi-asserted-by":"publisher","first-page":"245","DOI":"10.1007\/s11721-019-00171-0","volume":"13","author":"C Scheepers","year":"2019","unstructured":"Scheepers, C., Engelbrecht, A.P., Cleghorn, C.W.: Multi-guide particle swarm optimization for multi-objective optimization: empirical and stability analysis. Swarm Intell. 13(3), 245\u2013276 (2019). https:\/\/doi.org\/10.1007\/s11721-019-00171-0","journal-title":"Swarm Intell."},{"key":"8_CR15","unstructured":"Shi, Y., Eberhart, R.: The 1998 IEEE International Conference On Evolutionary Computation Proceedings (1998)"},{"issue":"4","key":"8_CR16","first-page":"407","volume":"1","author":"IM Sobol","year":"1993","unstructured":"Sobol, I.M.: Sensitivity estimates for nonlinear mathematical models. Math. Model. Comput. Exp. 1(4), 407\u2013414 (1993)","journal-title":"Math. Model. Comput. Exp."},{"issue":"2","key":"8_CR17","doi-asserted-by":"publisher","first-page":"173","DOI":"10.1109\/TEVC.2018.2791283","volume":"23","author":"Y Sun","year":"2018","unstructured":"Sun, Y., Yen, G.G., Yi, Z.: IGD indicator-based evolutionary algorithm for many-objective optimization problems. IEEE Trans. Evol. Comput. 23(2), 173\u2013187 (2018)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"8_CR18","unstructured":"Tapia, M., Coello, C.: Applications of multi-objective evolutionary algorithms in economics and finance: a survey. In: IEEE Congress on Evolutionary Computation, pp. 532\u2013539 (2007)"}],"container-title":["Lecture Notes in Computer Science","Swarm Intelligence"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-60376-2_8","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,16]],"date-time":"2024-08-16T08:00:39Z","timestamp":1723795239000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-60376-2_8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030603755","9783030603762"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-60376-2_8","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":"23 October 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ANTS","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":"Barcelona","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","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":"26 October 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 October 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"antsw2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.swarm-intelligence.eu\/ants2020\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}