{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T18:23:05Z","timestamp":1770747785254,"version":"3.49.0"},"reference-count":19,"publisher":"SAGE Publications","issue":"5","license":[{"start":{"date-parts":[[2015,7,29]],"date-time":"2015-07-29T00:00:00Z","timestamp":1438128000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"published-print":{"date-parts":[[2015,7,29]]},"abstract":"<jats:p>A dynamic version of Environmental Adaption Method (EAM) is proposed in this paper. Environmental Adaption Method for Dynamic Environment (EAMD) is an improvement over EAM, which works in dynamic environment with real valued parameters. Unlike EAM the theory of this algorithm is based on adaption of species in dynamic environment which gradually becomes more verse and deadly for their denizens. The species which are able to adapt in the changing environment, improves their fitness value by enhancing their phenotypic structure in the upcoming generations. Sudden and gradual dynamic changes in the environment assist species to converge towards the optimal fitness. Unlike EAM, EAMD is suitable for both unimodal and multimodal problems without the need of an alteration operator as there is enough diversity since the adaption is randomized, i.e. each possible solution can adapt anywhere within the search space. EAMD is compared with various algorithms tested on 24 benchmark functions against the Black Box Optimization Benchmarking (BBOB) test-bed at different dimensions with very promising results and EAMD shows its superiority over other state-of-the-art algorithms.<\/jats:p>","DOI":"10.3233\/ifs-151678","type":"journal-article","created":{"date-parts":[[2015,11,10]],"date-time":"2015-11-10T11:35:46Z","timestamp":1447155346000},"page":"2003-2015","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":2,"title":["An Environmental Adaption Method with real parameter encoding for dynamic environment"],"prefix":"10.1177","volume":"29","author":[{"given":"Ashish","family":"Tripathi","sequence":"first","affiliation":[{"name":"Computer Science and Engineering Department, MNNIT Allahabad, Uttar Pradesh, India"}]},{"given":"Nitin","family":"Saxena","sequence":"additional","affiliation":[{"name":"Computer Science and Engineering Department, MNNIT Allahabad, Uttar Pradesh, India"}]},{"given":"Krishn Kumar","family":"Mishra","sequence":"additional","affiliation":[{"name":"Computer Science and Engineering Department, MNNIT Allahabad, Uttar Pradesh, India"}]},{"given":"Arun Kumar","family":"Misra","sequence":"additional","affiliation":[{"name":"Computer Science and Engineering Department, MNNIT Allahabad, Uttar Pradesh, India"}]}],"member":"179","published-online":{"date-parts":[[2015,8,27]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"crossref","unstructured":"Mishra KK Tiwari S Misra AK 2011 A bio inspired algorithm for solving optimization problems Computer and Communication Technology (ICCCT) 2011 2nd International Conference on 653 659 IEEE","DOI":"10.1109\/ICCCT.2011.6075211"},{"key":"e_1_3_2_3_2","doi-asserted-by":"crossref","unstructured":"Mishra KK Tiwari S Misra AK 2012 Improved Environmental Adaption Method for Solving Optimization Problemsp Computational Intelligence and Intelligent Systems 300 313 Springer Berlin Heidelberg","DOI":"10.1007\/978-3-642-34289-9_34"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1086\/276428"},{"key":"e_1_3_2_5_2","unstructured":"http:\/\/coco.gforge.inria.fr\/"},{"key":"e_1_3_2_6_2","doi-asserted-by":"crossref","unstructured":"Holtschulte Neal J Moses M 2013 Benchmarking cellular genetic algorithms on the BBOB noiseless testbed Proceeding of the Fifteenth Annual Conference Companion on Genetic and Evolutionary Computation Conference Companion 1201 1208 ACM","DOI":"10.1145\/2464576.2482699"},{"key":"e_1_3_2_7_2","doi-asserted-by":"crossref","unstructured":"Alba Enrique Dorronsoro Bernab\u00e9 2009 Cellular genetic algorithms 42 Springer","DOI":"10.1007\/978-0-387-77610-1_1"},{"key":"e_1_3_2_8_2","doi-asserted-by":"crossref","unstructured":"Tran 2013 Multiobjectivization with NSGA-II on the noiseless BBOB testbed Proceeding of the Fifteenth Annual Conference Companion on Genetic and Evolutionary Computation Conference Companion 1217 1224 ACM","DOI":"10.1145\/2464576.2482700"},{"key":"e_1_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.1109\/4235.996017"},{"key":"e_1_3_2_10_2","unstructured":"Auger Anne Ros Raymond BBO-Benchmarking of Pure Random Search for Noiseless Function Testbed"},{"key":"e_1_3_2_11_2","doi-asserted-by":"crossref","unstructured":"Sawyerr 2013 Benchmarking projection-based real coded genetic algorithm on BBOB-noiseless function testbed Proceeding of the Fifteenth Annual Conference Companion on Genetic and Evolutionary Computation Conference Companion 1193 1200 ACM","DOI":"10.1145\/2464576.2482698"},{"key":"e_1_3_2_12_2","unstructured":"Sawyerr BA 2010 Hybrid real coded genetic algorithms with pattern search and projection University of Lagos Lagos Nigeria PhD thesis"},{"key":"e_1_3_2_13_2","doi-asserted-by":"publisher","DOI":"10.1080\/10556788.2010.491865"},{"key":"e_1_3_2_14_2","unstructured":"Cant\u2019u-Paz Erick Goldberg DE 1999 Parallel genetic algorithms with distributed panmictic populations"},{"key":"e_1_3_2_15_2","doi-asserted-by":"crossref","unstructured":"Tripathi Ashish 2014 Environmental adaption method for dynamic environment Systems Man and Cybernetics (SMC) IEEE International Conference on IEEE","DOI":"10.1109\/SMC.2014.6973910"},{"key":"e_1_3_2_16_2","doi-asserted-by":"crossref","unstructured":"B\u00e4ck Thomas 1996 Evolutionary algorithms in theory and practice: Evolution strategies evolutionary programming genetic algorithms Oxford university press","DOI":"10.1093\/oso\/9780195099713.001.0001"},{"key":"e_1_3_2_17_2","unstructured":"http:\/\/coco.gforge.inria.fr\/doku.php?id=bbob-2009"},{"key":"e_1_3_2_18_2","unstructured":"S. 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