LEADER 03393nam 22005415 450 001 9910483117003321 005 20200704014446.0 010 $a3-319-95104-1 024 7 $a10.1007/978-3-319-95104-1 035 $a(CKB)4100000005820389 035 $a(DE-He213)978-3-319-95104-1 035 $a(MiAaPQ)EBC5927129 035 $a(PPN)229914985 035 $a(EXLCZ)994100000005820389 100 $a20180818d2019 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aBioinspired Heuristics for Optimization /$fedited by El-Ghazali Talbi, Amir Nakib 205 $a1st ed. 2019. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019. 215 $a1 online resource (VIII, 314 p. 97 illus., 52 illus. in color.) 225 1 $aStudies in Computational Intelligence,$x1860-949X ;$v774 311 $a3-319-95103-3 320 $aIncludes bibliographical references. 327 $aPossibilistic Framework for Multi-objective Optimization under Uncertainty -- Solving the Uncapacitated Single Allocation p-Hub Median Problem on GPU. Phase Equilibrium Description of a Supercritical Extraction System using Metaheuristic Optimization Algorithms -- Intrusion Detection System based on a behavioral approach -- A new hybrid method to solve the multi-objective optimization problem for a composite hat-stiffened panel -- Storage yard management: modelling and solving -- Multi-capacitated location problem : A new resolution method combining exact and heuristic approaches based on set partitioning -- Application of genetic algorithm for solving bilevel linear programming problems -- Adapted Bin-Packing algorithm for the yard optimization problem -- Hidden Markov Model classi?er for the adaptive ACS-TSP pheromone parameters. 330 $aThis book presents recent research on bioinspired heuristics for optimization. Learning- based and black-box optimization exhibit some properties of intrinsic parallelization, and can be used for various optimizations problems. Featuring the most relevant work presented at the 6th International Conference on Metaheuristics and Nature Inspired Computing, held at Marrakech (Morocco) from 27th to 31st October 2016, the book presents solutions, methods, algorithms, case studies, and software. It is a valuable resource for research academics and industrial practitioners. 410 0$aStudies in Computational Intelligence,$x1860-949X ;$v774 606 $aComputational intelligence 606 $aArtificial intelligence 606 $aComputational Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/T11014 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 615 0$aComputational intelligence. 615 0$aArtificial intelligence. 615 14$aComputational Intelligence. 615 24$aArtificial Intelligence. 676 $a006.38 702 $aTalbi$b El-Ghazali$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aNakib$b Amir$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910483117003321 996 $aBioinspired Heuristics for Optimization$92844391 997 $aUNINA LEADER 01370nas 2200421-a 450 001 9910339729003321 005 20241221110603.0 035 $a(CKB)111030132181000 035 $a(CONSER)--2001215178 035 $a(MiFhGG)0JSR 035 $a(EXLCZ)99111030132181000 100 $a20010725a20019999 --- a 101 0 $aeng 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aAdweek Magazine's technology marketing 210 $aNew York, NY $cB.P.I. Communications, Inc.$d2001- 215 $a1 online resource 300 $aTitle from cover. 311 08$aPrint version: Adweek Magazine's technology marketing. 1536-2272 (DLC) 2001215178 (OCoLC)476427390 531 0 $aAdweek mag. tech. market. 606 $aComputers$xMarketing$vPeriodicals 606 $aComputer industry$vPeriodicals 606 $aComputer industry$2fast$3(OCoLC)fst00872154 606 $aComputers$xMarketing$2fast$3(OCoLC)fst00872831 608 $aPeriodicals.$2fast 608 $aPeriodicals.$2lcgft 615 0$aComputers$xMarketing 615 0$aComputer industry 615 7$aComputer industry. 615 7$aComputers$xMarketing. 676 $a004 906 $aJOURNAL 912 $a9910339729003321 920 $aexl_impl conversion 996 $aAdweek Magazine's technology marketing$92562161 997 $aUNINA