LEADER 03869nam  22006015  450 
001 9910483057703321
005 20251002143429.0
010   $a981-336-710-5
024 7 $a10.1007/978-981-33-6710-4
035   $a(CKB)4100000011881102
035   $a(MiAaPQ)EBC6550494
035   $a(Au-PeEL)EBL6550494
035   $a(OCoLC)1246581553
035   $a(PPN)255295278
035   $a(DE-He213)978-981-33-6710-4
035   $a(EXLCZ)994100000011881102
100   $a20210412d2021      u|         0
101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aConstraint Handling in Metaheuristics and Applications /$fedited by Anand J. Kulkarni, Efrén Mezura-Montes, Yong Wang, Amir H. Gandomi, Ganesh Krishnasamy
205   $a1st ed. 2021.
210  1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2021.
215   $a1 online resource (336 pages)
225 1 $aComputer Science Series
311 08$a981-336-709-1 
320   $aIncludes bibliographical references and index.
327   $a1. The Find-Fix-Finish-Exploit-Analyze (F3EA) meta-heuristic algorithm with an extended constraint handling technique for constrained optimization and engineering design -- An improved Cohort Intelligence with Panoptic Learning Behavior for solving constrained problems -- Nature-Inspired Metaheuristic Algorithms for Constraint Handling: Challenges, Issues and Research Perspective.
330   $aThis book aims to discuss the core and underlying principles and analysis of the different constraint handling approaches. The main emphasis of the book is on providing an enriched literature on mathematical modelling of the test as well as real-world problems with constraints, and further development of generalized constraint handling techniques. These techniques may be incorporated in suitable metaheuristics providing a solid optimized solution to the problems and applications being addressed. The book comprises original contributions with an aim to develop and discuss generalized constraint handling approaches/techniques for the metaheuristics and/or the applications being addressed. A variety of novel as well as modified and hybridized techniques have been discussed in the book. The conceptual as well as the mathematical level in all the chapters is well within the grasp of the scientists as well as the undergraduate and graduate students from the engineering and computer science streams. The reader is encouraged to have basic knowledge of probability and mathematical analysis and optimization. The book also provides critical review of the contemporary constraint handling approaches. The contributions of the book may further help to explore new avenues leading towards multidisciplinary research discussions. This book is a complete reference for engineers, scientists, and students studying/working in the optimization, artificial intelligence (AI), or computational intelligence arena. .
410  0$aComputer Science Series
606   $aArtificial intelligence
606   $aMathematical models
606   $aComputational intelligence
606   $aArtificial Intelligence
606   $aMathematical Modeling and Industrial Mathematics
606   $aComputational Intelligence
615  0$aArtificial intelligence.
615  0$aMathematical models.
615  0$aComputational intelligence.
615 14$aArtificial Intelligence.
615 24$aMathematical Modeling and Industrial Mathematics.
615 24$aComputational Intelligence.
676   $a005.11
702   $aKulkarni$b Anand Jayant
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910483057703321
996   $aConstraint handling in metaheuristics and applications$91901313
997   $aUNINA