Please use this identifier to cite or link to this item:
http://localhost/handle/Hannan/1243
Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Mandal, Jyotsna K. ; | en_US |
| dc.contributor.author | Mukhopadhyay, Somnath. ; | en_US |
| dc.contributor.author | Dutta, Paramartha. ; | en_US |
| dc.date.accessioned | 2013 | en_US |
| dc.date.accessioned | 2020-05-17T08:26:53Z | - |
| dc.date.available | 2020-05-17T08:26:53Z | - |
| dc.date.issued | 2018 | en_US |
| dc.identifier.isbn | 9789811314711 ; | en_US |
| dc.identifier.isbn | 9789811314704 (print) ; | en_US |
| dc.identifier.isbn | 9789811314728 (print) ; | en_US |
| dc.identifier.uri | http://localhost/handle/Hannan/1243 | - |
| dc.description | SpringerLink (Online service) ; | en_US |
| dc.description | en_US | |
| dc.description | en_US | |
| dc.description | en_US | |
| dc.description | Printed edition: ; 9789811314704. ; | en_US |
| dc.description | en_US | |
| dc.description | Printed edition: ; 9789811314728. ; | en_US |
| dc.description | en_US | |
| dc.description.abstract | This 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. ; | en_US |
| dc.description.statementofresponsibility | edited by Jyotsna K. Mandal, Somnath Mukhopadhyay, Paramartha Dutta. | en_US |
| dc.description.tableofcontents | Chapter 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 ee 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 ee 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. ; | en_US |
| dc.format.extent | XVI, 318 p. 90 illus., 51 illus. in color. ; online resource. ; | en_US |
| dc.publisher | Springer Singapore : | en_US |
| dc.publisher | Imprint: Springer, | en_US |
| dc.relation.haspart | 9789811314704.pdf | en_US |
| dc.subject | Computer Science | en_US |
| dc.subject | Mathematical optimization. ; | en_US |
| dc.subject | Engineering | en_US |
| dc.subject | Mathematics of Computing. ; http://scigraph.springernature.com/things/product-market-codes/I17001. ; | en_US |
| dc.subject | Optimization. ; http://scigraph.springernature.com/things/product-market-codes/M26008. ; | en_US |
| dc.subject | Computational Intelligence. ; http://scigraph.springernature.com/things/product-market-codes/T11014. ; | en_US |
| dc.subject.ddc | 004.0151 ; 23 ; | en_US |
| dc.subject.lcc | QA76.9.M35 ; | en_US |
| dc.title | Multi-Objective Optimization | en_US |
| dc.title.alternative | Evolutionary to Hybrid Framework / | en_US |
| dc.type | Book | en_US |
| dc.publisher.place | Singapore : | en_US |
| Appears in Collections: | مدیریت فناوری اطلاعات | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 9789811314704.pdf | 10.85 MB | Adobe PDF |  Preview File |
Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Mandal, Jyotsna K. ; | en_US |
| dc.contributor.author | Mukhopadhyay, Somnath. ; | en_US |
| dc.contributor.author | Dutta, Paramartha. ; | en_US |
| dc.date.accessioned | 2013 | en_US |
| dc.date.accessioned | 2020-05-17T08:26:53Z | - |
| dc.date.available | 2020-05-17T08:26:53Z | - |
| dc.date.issued | 2018 | en_US |
| dc.identifier.isbn | 9789811314711 ; | en_US |
| dc.identifier.isbn | 9789811314704 (print) ; | en_US |
| dc.identifier.isbn | 9789811314728 (print) ; | en_US |
| dc.identifier.uri | http://localhost/handle/Hannan/1243 | - |
| dc.description | SpringerLink (Online service) ; | en_US |
| dc.description | en_US | |
| dc.description | en_US | |
| dc.description | en_US | |
| dc.description | Printed edition: ; 9789811314704. ; | en_US |
| dc.description | en_US | |
| dc.description | Printed edition: ; 9789811314728. ; | en_US |
| dc.description | en_US | |
| dc.description.abstract | This 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. ; | en_US |
| dc.description.statementofresponsibility | edited by Jyotsna K. Mandal, Somnath Mukhopadhyay, Paramartha Dutta. | en_US |
| dc.description.tableofcontents | Chapter 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 ee 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 ee 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. ; | en_US |
| dc.format.extent | XVI, 318 p. 90 illus., 51 illus. in color. ; online resource. ; | en_US |
| dc.publisher | Springer Singapore : | en_US |
| dc.publisher | Imprint: Springer, | en_US |
| dc.relation.haspart | 9789811314704.pdf | en_US |
| dc.subject | Computer Science | en_US |
| dc.subject | Mathematical optimization. ; | en_US |
| dc.subject | Engineering | en_US |
| dc.subject | Mathematics of Computing. ; http://scigraph.springernature.com/things/product-market-codes/I17001. ; | en_US |
| dc.subject | Optimization. ; http://scigraph.springernature.com/things/product-market-codes/M26008. ; | en_US |
| dc.subject | Computational Intelligence. ; http://scigraph.springernature.com/things/product-market-codes/T11014. ; | en_US |
| dc.subject.ddc | 004.0151 ; 23 ; | en_US |
| dc.subject.lcc | QA76.9.M35 ; | en_US |
| dc.title | Multi-Objective Optimization | en_US |
| dc.title.alternative | Evolutionary to Hybrid Framework / | en_US |
| dc.type | Book | en_US |
| dc.publisher.place | Singapore : | en_US |
| Appears in Collections: | مدیریت فناوری اطلاعات | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 9789811314704.pdf | 10.85 MB | Adobe PDF | Preview File |
Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Mandal, Jyotsna K. ; | en_US |
| dc.contributor.author | Mukhopadhyay, Somnath. ; | en_US |
| dc.contributor.author | Dutta, Paramartha. ; | en_US |
| dc.date.accessioned | 2013 | en_US |
| dc.date.accessioned | 2020-05-17T08:26:53Z | - |
| dc.date.available | 2020-05-17T08:26:53Z | - |
| dc.date.issued | 2018 | en_US |
| dc.identifier.isbn | 9789811314711 ; | en_US |
| dc.identifier.isbn | 9789811314704 (print) ; | en_US |
| dc.identifier.isbn | 9789811314728 (print) ; | en_US |
| dc.identifier.uri | http://localhost/handle/Hannan/1243 | - |
| dc.description | SpringerLink (Online service) ; | en_US |
| dc.description | en_US | |
| dc.description | en_US | |
| dc.description | en_US | |
| dc.description | Printed edition: ; 9789811314704. ; | en_US |
| dc.description | en_US | |
| dc.description | Printed edition: ; 9789811314728. ; | en_US |
| dc.description | en_US | |
| dc.description.abstract | This 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. ; | en_US |
| dc.description.statementofresponsibility | edited by Jyotsna K. Mandal, Somnath Mukhopadhyay, Paramartha Dutta. | en_US |
| dc.description.tableofcontents | Chapter 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 ee 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 ee 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. ; | en_US |
| dc.format.extent | XVI, 318 p. 90 illus., 51 illus. in color. ; online resource. ; | en_US |
| dc.publisher | Springer Singapore : | en_US |
| dc.publisher | Imprint: Springer, | en_US |
| dc.relation.haspart | 9789811314704.pdf | en_US |
| dc.subject | Computer Science | en_US |
| dc.subject | Mathematical optimization. ; | en_US |
| dc.subject | Engineering | en_US |
| dc.subject | Mathematics of Computing. ; http://scigraph.springernature.com/things/product-market-codes/I17001. ; | en_US |
| dc.subject | Optimization. ; http://scigraph.springernature.com/things/product-market-codes/M26008. ; | en_US |
| dc.subject | Computational Intelligence. ; http://scigraph.springernature.com/things/product-market-codes/T11014. ; | en_US |
| dc.subject.ddc | 004.0151 ; 23 ; | en_US |
| dc.subject.lcc | QA76.9.M35 ; | en_US |
| dc.title | Multi-Objective Optimization | en_US |
| dc.title.alternative | Evolutionary to Hybrid Framework / | en_US |
| dc.type | Book | en_US |
| dc.publisher.place | Singapore : | en_US |
| Appears in Collections: | مدیریت فناوری اطلاعات | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 9789811314704.pdf | 10.85 MB | Adobe PDF | Preview File |