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010   $a981-13-1471-3
010   $a9789811314711
024 7 $a10.1007/978-981-13-1471-1
035   $a(CKB)4100000008525667
035   $a(MiAaPQ)EBC5495489
035   $a(DE-He213)978-981-13-1471-1
035   $a(PPN)229913806
035   $a(EXLCZ)994100000008525667
100   $a20180818d2018      u|         0
101 0 $aeng
135   $aurnn|008mamaa
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aMulti-Objective Optimization $eEvolutionary to Hybrid Framework /$fedited by Jyotsna K. Mandal, Somnath Mukhopadhyay, Paramartha Dutta
205   $a1st ed. 2018.
210  1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2018.
215   $a1 online resource (XVI, 318 p. 90 illus., 51 illus. in color.) 
311 08$a981-13-1470-5 
327   $aChapter 1. An Advance Overview of Single and Multi-Objective Optimization -- Chapter 2. Non-dominated Sorting Based Multi/Many Objective Optimization: Two Decades of Research and Application -- Chapter 3. Uncertain Multi-objective Portfolio Selection Model based on Genetic Algorithm -- Chapter 4. A Multiobjective Genetic Algorithm-based Approach for Identifying Relevant and Non-redundant Cancer-MicroRNA Markers -- Chapter 5. Application of Multi-objective Optimizations in Protein Structure Prediction -- Chapter 6. Multi-target Multiobjective Programming and Patrol Manpower Planning for Traffic Management via Genetic Algorithm -- Chapter 7. Multi-objective Optimization for Key Player Identification in Networks -- Chapter 8. Joint Maximization in Energy and Spectral Efficiency in Cooperative Cognitive Radio Networks -- Chapter 9. A Neoteric Multi-Objective Framework for Engineering Process Optimization: Metaheuristics and Experimental Designs based Approach -- Chapter 10. Multi/Many Objective Optimization ? Hybrid Intelligent Framework -- Chapter 11. Efficiency Maximization of Multimedia Data Mining using Multiobjective Neuro-ACO Approach -- Chapter 12. Optimized Determination of Separating Hyper-Plane of an SVM ? Hybrid Multiobjective Model -- Chapter 13. Efficient Cluster Head Selection in Wireless Sensor Network using Multiobjective Model -- Chapter 14. Achieving Optimized Bio-Metric Security in E-Governance by Multiobjective Neuro Approach -- Chapter 15. Advantage of Quantum Inspired Multiobjective Genetic Algorithm over Classical Multiobjective Genetic Algorithm -- Chapter 16. Optimizing Performance Parameter of Image Segmentation using Hybrid Multiobjective Framework.
330   $aThis book brings together the latest findings on efficient solutions of multi/many-objective optimization problems from the leading researchers in the field. The focus is on solving real-world optimization problems using strategies ranging from evolutionary to hybrid frameworks, and involving various computation platforms. The topics covered include solution frameworks using evolutionary to hybrid models in application areas like Analytics, Cancer Research, Traffic Management, Networks and Communications, E-Governance, Quantum Technology, Image Processing, etc. As such, the book offers a valuable resource for all postgraduate students and researchers interested in exploring solution frameworks for multi/many-objective optimization problems.
606   $aComputer science$xMathematics
606   $aMathematical optimization
606   $aComputational intelligence
606   $aMathematics of Computing
606   $aOptimization
606   $aComputational Intelligence
615  0$aComputer science$xMathematics.
615  0$aMathematical optimization.
615  0$aComputational intelligence.
615 14$aMathematics of Computing.
615 24$aOptimization.
615 24$aComputational Intelligence.
676   $a004.0151
702   $aMandal$b Jyotsna K$4edt$4http://id.loc.gov/vocabulary/relators/edt
702   $aMukhopadhyay$b Somnath$4edt$4http://id.loc.gov/vocabulary/relators/edt
702   $aDutta$b Paramartha$4edt$4http://id.loc.gov/vocabulary/relators/edt
906   $aBOOK
912   $a9910349472603321
996   $aMulti-Objective Optimization$91963620
997   $aUNINA