LEADER 01149nam a2200277 a 4500 001 991000496369707536 008 040301s ne 000 0 eng d 020 $a9027250839 (Eur.) 020 $a1556199465 (US) (alk. paper) 035 $ab12625620-39ule_inst 040 $aDip.to Lingue $bita 100 1 $aArnovick, Leslie K.$0482156 245 10$aDiachronic pragmatics:$bseven case studies in english illocutionary development;$cLeslie K. Arnovick, University of British Columbia 260 $aAmsterdam/Philadelphia :$bJohn Benjamins Publishing Company,$cc1999 300 $a191 p. ;$c22 cm. 400 0$aPragmatics & Beyond new series,$vv.68 504 $aIncludes bibliographical references and index 546 $aInglese 650 14$aLingua inglese$xAnalisi del discorso 650 24$aLingua inglese$xGrammatica storica 907 $a.b12625620$b21-09-06$c01-03-04 912 $a991000496369707536 945 $aLE012 420.141 ARN$g1$i2012000043442$lle012$o-$pE0.00$q-$rl$s- $t0$u1$v0$w1$x0$y.i13119734$z01-03-04 996 $aDiachronic pragmatics$9276036 997 $aUNISALENTO 998 $ale012$b - - $cm$da $e-$feng$gne $h0$i1 LEADER 05391nam 2201369z- 450 001 9910557699203321 005 20220111 035 $a(CKB)5400000000044565 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/77036 035 $a(oapen)doab77036 035 $a(EXLCZ)995400000000044565 100 $a20202201d2021 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aEvolutionary Computation 2020 210 $aBasel, Switzerland$cMDPI - Multidisciplinary Digital Publishing Institute$d2021 215 $a1 online resource (442 p.) 311 08$a3-0365-2394-4 311 08$a3-0365-2395-2 330 $aIntelligent optimization is based on the mechanism of computational intelligence to refine a suitable feature model, design an effective optimization algorithm, and then to obtain an optimal or satisfactory solution to a complex problem. Intelligent algorithms are key tools to ensure global optimization quality, fast optimization efficiency and robust optimization performance. Intelligent optimization algorithms have been studied by many researchers, leading to improvements in the performance of algorithms such as the evolutionary algorithm, whale optimization algorithm, differential evolution algorithm, and particle swarm optimization. Studies in this arena have also resulted in breakthroughs in solving complex problems including the green shop scheduling problem, the severe nonlinear problem in one-dimensional geodesic electromagnetic inversion, error and bug finding problem in software, the 0-1 backpack problem, traveler problem, and logistics distribution center siting problem. The editors are confident that this book can open a new avenue for further improvement and discoveries in the area of intelligent algorithms. The book is a valuable resource for researchers interested in understanding the principles and design of intelligent algorithms. 606 $aTechnology: general issues$2bicssc 610 $a0-1 knapsack problem 610 $aant colony optimization 610 $aassortative mating 610 $abinary whale optimization algorithm 610 $abug detection 610 $abWOA-S 610 $abWOA-V 610 $acitation 610 $aclassification 610 $acoevolution 610 $aconstrained optimization 610 $acuckoo search algorithm 610 $adecomposition-based multi-objective optimisation 610 $adifferential evolution 610 $adimensionality reduction 610 $adiscrete artificial bee colony algorithm 610 $adiversity preservation 610 $adominance 610 $adynamic learning 610 $aelephant herding optimization 610 $aengineering optimization 610 $aevolutionary algorithm 610 $aevolutionary algorithms (EAs) 610 $aevolutionary computation 610 $afeature selection 610 $afuzzing 610 $afuzzy hybrid flow shop scheduling 610 $agame feature 610 $agame simulation 610 $agame trees 610 $ageoelectric model 610 $aglobal optimization 610 $agreen shop scheduling 610 $agrey wolf optimizer 610 $ah-index 610 $aiterated local search 610 $aknapsack problem 610 $aknowledge transfer 610 $akrill herd 610 $amagnetotelluric 610 $amany-objective optimization 610 $amemetic algorithm 610 $amenu planning problem 610 $ametaheuristic 610 $aminimize makespan 610 $aminimize total energy consumption 610 $amulti-indicators 610 $amulti-metric 610 $amulti-objective optimization 610 $amulti-resources 610 $amulti-task evolutionary computation 610 $amulti-task optimization 610 $amutation 610 $aone-dimensional inversions 610 $aopposite path 610 $aopposition-based learning 610 $aoptimization problem 610 $aPareto optimality 610 $aPareto-front 610 $aparticle swarm optimization 610 $apath discovery 610 $aperformance indicators 610 $aplaytesting 610 $aplaytesting metric 610 $apremature convergence 610 $aQ-learning 610 $aquantum 610 $aquantum computing 610 $aranking 610 $aseed schedule 610 $aself-adaptive step size 610 $asimulated annealing 610 $asingle objective optimization 610 $asingle-objective optimization 610 $asuccess-history 610 $aswarm intelligence 610 $atraveling salesman problems 610 $atravelling salesman problem 610 $aturning-based mutation 610 $aunified search space 610 $auniversities ranking 610 $avalidation 610 $awhale optimization algorithm 610 $aWOA 615 7$aTechnology: general issues 700 $aWang$b Gai-Ge$4edt$01322388 702 $aAlavi$b Amir$4edt 702 $aWang$b Gai-Ge$4oth 702 $aAlavi$b Amir$4oth 906 $aBOOK 912 $a9910557699203321 996 $aEvolutionary Computation 2020$93034943 997 $aUNINA