{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,5]],"date-time":"2025-10-05T04:23:59Z","timestamp":1759638239575,"version":"3.40.3"},"publisher-location":"Cham","reference-count":21,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030729035"},{"type":"electronic","value":"9783030729042"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"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":[[2021]]},"DOI":"10.1007\/978-3-030-72904-2_10","type":"book-chapter","created":{"date-parts":[[2021,3,26]],"date-time":"2021-03-26T11:03:03Z","timestamp":1616756583000},"page":"152-168","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Stagnation Detection with Randomized Local Search"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0898-5003","authenticated-orcid":false,"given":"Amirhossein","family":"Rajabi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6105-7700","authenticated-orcid":false,"given":"Carsten","family":"Witt","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,3,27]]},"reference":[{"key":"10_CR1","doi-asserted-by":"crossref","unstructured":"Bassin, A., Buzdalov, M.: The 1\/5-th rule with rollbacks: on self-adjustment of the population size in the (1+($$\\lambda $$, $$\\lambda $$)) GA. In: Proceedings of GECCO 2019 (Companion), pp. 277\u2013278. ACM Press (2019)","DOI":"10.1145\/3319619.3322067"},{"key":"10_CR2","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1007\/978-3-319-99259-4_6","volume-title":"Parallel Problem Solving from Nature \u2013 PPSN XV","author":"D Corus","year":"2018","unstructured":"Corus, D., Oliveto, P.S., Yazdani, D.: Fast artificial immune systems. In: Auger, A., Fonseca, C.M., Louren\u00e7o, N., Machado, P., Paquete, L., Whitley, D. (eds.) PPSN 2018. LNCS, vol. 11102, pp. 67\u201378. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-99259-4_6"},{"key":"10_CR3","series-title":"Natural Computing Series","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/978-3-030-29414-4_1","volume-title":"Theory of Evolutionary Computation","author":"B Doerr","year":"2020","unstructured":"Doerr, B.: Probabilistic tools for the analysis of randomized optimization heuristics. In: Doerr, B., Neumann, F. (eds.) Theory of Evolutionary Computation. NCS, pp. 1\u201387. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-29414-4_1"},{"issue":"3","key":"10_CR4","doi-asserted-by":"publisher","first-page":"529","DOI":"10.1007\/s00453-015-0019-5","volume":"75","author":"B Doerr","year":"2016","unstructured":"Doerr, B., Doerr, C.: The impact of random initialization on the runtime of randomized search heuristics. Algorithmica 75(3), 529\u2013553 (2016)","journal-title":"Algorithmica"},{"issue":"5","key":"10_CR5","doi-asserted-by":"publisher","first-page":"1658","DOI":"10.1007\/s00453-017-0354-9","volume":"80","author":"B Doerr","year":"2018","unstructured":"Doerr, B., Doerr, C.: Optimal static and self-adjusting parameter choices for the (1+($$\\lambda $$, $$\\lambda $$)) genetic algorithm. Algorithmica 80(5), 1658\u20131709 (2018)","journal-title":"Algorithmica"},{"key":"10_CR6","series-title":"Natural Computing Series","doi-asserted-by":"publisher","first-page":"271","DOI":"10.1007\/978-3-030-29414-4_6","volume-title":"Theory of Evolutionary Computation","author":"B Doerr","year":"2020","unstructured":"Doerr, B., Doerr, C.: Theory of parameter control for discrete black-box optimization: provable performance gains through dynamic parameter choices. In: Doerr, B., Neumann, F. (eds.) Theory of Evolutionary Computation. NCS, pp. 271\u2013321. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-29414-4_6"},{"key":"10_CR7","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"824","DOI":"10.1007\/978-3-319-45823-6_77","volume-title":"Parallel Problem Solving from Nature \u2013 PPSN XIV","author":"B Doerr","year":"2016","unstructured":"Doerr, B., Doerr, C., Yang, J.: $$k$$-bit mutation with self-adjusting $$k$$ outperforms standard bit mutation. In: Handl, J., Hart, E., Lewis, P.R., L\u00f3pez-Ib\u00e1\u00f1ez, M., Ochoa, G., Paechter, B. (eds.) PPSN 2016. LNCS, vol. 9921, pp. 824\u2013834. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-45823-6_77"},{"key":"10_CR8","doi-asserted-by":"crossref","unstructured":"Doerr, B., Fouz, M., Witt, C.: Quasirandom evolutionary algorithms. In: Proceedings of GECCO 2010, pp. 1457\u20131464. ACM (2010)","DOI":"10.1145\/1830483.1830749"},{"issue":"2","key":"10_CR9","doi-asserted-by":"publisher","first-page":"593","DOI":"10.1007\/s00453-018-0502-x","volume":"81","author":"B Doerr","year":"2019","unstructured":"Doerr, B., Gie\u00dfen, C., Witt, C., Yang, J.: The (1 + $$\\lambda $$) evolutionary algorithm with self-adjusting mutation rate. Algorithmica 81(2), 593\u2013631 (2019)","journal-title":"Algorithmica"},{"key":"10_CR10","doi-asserted-by":"crossref","unstructured":"Doerr, B., Jansen, T., Klein, C.: Comparing global and local mutations on bit strings. In: Ryan, C., Keijzer, M. (eds.) Proceedings of GECCO 2008, pp. 929\u2013936. ACM Press (2008)","DOI":"10.1145\/1389095.1389274"},{"key":"10_CR11","doi-asserted-by":"crossref","unstructured":"Doerr, B., Le, H.P., Makhmara, R., Nguyen, T.D.: Fast genetic algorithms. In: Proceedings of GECCO 2017, pp. 777\u2013784. ACM Press (2017)","DOI":"10.1145\/3071178.3071301"},{"key":"10_CR12","series-title":"International Series in Operations Research & Management Science","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1007\/978-3-319-91086-4_3","volume-title":"Handbook of Metaheuristics","author":"P Hansen","year":"2019","unstructured":"Hansen, P., Mladenovi\u0107, N., Brimberg, J., P\u00e9rez, J.A.M.: Variable neighborhood search. In: Gendreau, M., Potvin, J.-Y. (eds.) Handbook of Metaheuristics. ISORMS, vol. 272, pp. 57\u201397. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-319-91086-4_3"},{"key":"10_CR13","doi-asserted-by":"crossref","unstructured":"Lissovoi, A., Oliveto, P.S., Warwicker, J.A.: On the time complexity of algorithm selection hyper-heuristics for multimodal optimisation. In: Proceedings of AAAI 2019, pp. 2322\u20132329. AAAI Press (2019)","DOI":"10.1609\/aaai.v33i01.33012322"},{"key":"10_CR14","unstructured":"Lugo, M.: Sum of \u201cthe first $$k$$\u201d binomial coefficients for fixed $$n$$. MathOverflow (2017). https:\/\/mathoverflow.net\/q\/17236. Accessed 15 Mar 2021"},{"key":"10_CR15","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1016\/j.tcs.2006.11.002","volume":"378","author":"F Neumann","year":"2007","unstructured":"Neumann, F., Wegener, I.: Randomized local search, evolutionary algorithms, and the minimum spanning tree problem. Theoretical Comput. Sci. 378, 32\u201340 (2007)","journal-title":"Theoretical Comput. Sci."},{"issue":"2","key":"10_CR16","doi-asserted-by":"publisher","first-page":"145","DOI":"10.1109\/TEVC.2006.871251","volume":"10","author":"GR Raidl","year":"2006","unstructured":"Raidl, G.R., Koller, G., Julstrom, B.A.: Biased mutation operators for subgraph-selection problems. IEEE Trans. Evol. Comput. 10(2), 145\u2013156 (2006)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"10_CR17","doi-asserted-by":"crossref","unstructured":"Rajabi, A., Witt, C.: Self-adjusting evolutionary algorithms for multimodal optimization. In: Proceedings of GECCO 2020, pp. 1314\u20131322. ACM Press (2020)","DOI":"10.1145\/3377930.3389833"},{"key":"10_CR18","unstructured":"Rajabi, A., Witt, C.: Stagnation detection with randomized local search (2021). CoRR abs\/2101.12054. http:\/\/arxiv.org\/abs\/2101.12054"},{"key":"10_CR19","unstructured":"Warwicker, J.A.: On the runtime analysis of selection hyper-heuristics for pseudo-Boolean optimisation. Ph.D. thesis, University of Sheffield, UK (2019). http:\/\/ethos.bl.uk\/OrderDetails.do?uin=uk.bl.ethos.786561"},{"key":"10_CR20","unstructured":"Wegener, I.: Methods for the analysis of evolutionary algorithms on pseudo-Boolean functions. In: Sarker, R., Mohammadian, M., Yao, X. (eds.) Evolutionary Optimization. Kluwer Academic Publishers, New York (2001)"},{"key":"10_CR21","doi-asserted-by":"crossref","unstructured":"Witt, C.: Revised analysis of the (1+1) EA for the minimum spanning tree problem. In: Proceedings of GECCO 2014, pp. 509\u2013516. ACM Press (2014)","DOI":"10.1145\/2576768.2598237"}],"container-title":["Lecture Notes in Computer Science","Evolutionary Computation in Combinatorial Optimization"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-72904-2_10","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,3,31]],"date-time":"2021-03-31T23:06:34Z","timestamp":1617231994000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-72904-2_10"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030729035","9783030729042"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-72904-2_10","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"27 March 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"EvoCOP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Evolutionary Computation in Combinatorial Optimization (Part of EvoStar)","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 April 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9 April 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"evocop2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.evostar.org\/2021\/evocop\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}