LEADER 03275nam 22006615 450 001 9910734094603321 005 20230719192512.0 010 $a3-319-07407-5 024 7 $a10.1007/978-3-319-07407-8 035 $a(CKB)3710000000521514 035 $a(EBL)4179463 035 $a(SSID)ssj0001584291 035 $a(PQKBManifestationID)16265715 035 $a(PQKBTitleCode)TC0001584291 035 $a(PQKBWorkID)14866306 035 $a(PQKB)11309579 035 $a(DE-He213)978-3-319-07407-8 035 $a(MiAaPQ)EBC4179463 035 $a(PPN)19053270X 035 $a(EXLCZ)993710000000521514 100 $a20151127d2015 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aMultimodal Optimization by Means of Evolutionary Algorithms /$fby Mike Preuss 205 $a1st ed. 2015. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2015. 215 $a1 online resource (206 p.) 225 1 $aNatural Computing Series,$x2627-6461 300 $aDescription based upon print version of record. 311 $a3-319-07406-7 320 $aIncludes bibliographical references. 327 $aIntroduction: Towards Multimodal Optimization -- Experimentation in Evolutionary Computation -- Groundwork for Niching -- Nearest-Better Clustering -- Niching Methods and Multimodal Optimization Performance -- Nearest-Better Based Niching. 330 $aThis book offers the first comprehensive taxonomy for multimodal optimization algorithms, work with its root in topics such as niching, parallel evolutionary algorithms, and global optimization. The author explains niching in evolutionary algorithms and its benefits; he examines their suitability for use as diagnostic tools for experimental analysis, especially for detecting problem (type) properties; and he measures and compares the performances of niching and canonical EAs using different benchmark test problem sets. His work consolidates the recent successes in this domain, presenting and explaining use cases, algorithms, and performance measures, with a focus throughout on the goals of the optimization processes and a deep understanding of the algorithms used. The book will be useful for researchers and practitioners in the area of computational intelligence, particularly those engaged with heuristic search, multimodal optimization, evolutionary computing, and experimental analysis. 410 0$aNatural Computing Series,$x2627-6461 606 $aAlgorithms 606 $aComputational intelligence 606 $aMathematical optimization 606 $aAlgorithms 606 $aComputational Intelligence 606 $aOptimization 615 0$aAlgorithms. 615 0$aComputational intelligence. 615 0$aMathematical optimization. 615 14$aAlgorithms. 615 24$aComputational Intelligence. 615 24$aOptimization. 676 $a006.336 700 $aPreuss$b Mike$4aut$4http://id.loc.gov/vocabulary/relators/aut$01371380 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910734094603321 996 $aMultimodal Optimization by Means of Evolutionary Algorithms$93400413 997 $aUNINA