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[null,null,"Titolo",null,"Optimization, variational analysis and applications : IFSOVAA-2020, Varanasi, India, February 2-4 / / edited by Vivek Laha, Pierre Maréchal, and S. K. Mishra"]
[null,null,"Pubbl/distr/stampa",null,"Singapore : , : Springer, , [2021]"]
[{"$nulls":4},"©2021"]
[null,null,"ISBN",null,"981-16-1819-4"]
[null,null,"Descrizione fisica",null,"1 online resource (444 pages)"]
[null,null,"Collana",null,"Springer Proceedings in Mathematics and Statistics ; ; v.355"]
[null,null,"Disciplina",null,"620.00151564"]
[null,null,"Soggetti",null,"Calculus of variations"]
[{"$nulls":4},"Mathematical optimization"]
[{"$nulls":4},"Optimització matemàtica"]
[{"$nulls":4},"Càlcul de variacions"]
[{"$nulls":4},"Congressos"]
[{"$nulls":4},"Llibres electrònics"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Intro -- Foreword -- Preface -- Contents -- Contributors -- 1 Linear and Pascoletti-Serafini Scalarizations in Unified Set Optimization -- 1.1 Introduction -- 1.2 Preliminaries -- 1.3 Scalarization -- 1.4 Linear Scalarizations -- 1.5 Pascoletti-Serafini Scalarization Scheme -- 1.6 Conclusions -- References -- 2 A Gradient-Free Method for Multi-objective Optimization Problem -- 2.1 Introduction -- 2.2 Notations and Preliminaries -- 2.3 Gradient-Free Method for MOP -- 2.3.1 Modified Nelder-Mead Algorithm -- 2.4 Numerical Illustrations and Performance Assessment -- 2.5 Performance Profile -- 2.6 Conclusions -- References -- 3 The New Butterfly Relaxation Method for Mathematical Programs with Complementarity Constraints -- 3.1 Introduction -- 3.2 Preliminaries -- 3.2.1 Non-Linear Programming -- 3.2.2 Mathematical Programs with Complementarity Constraints -- 3.3 The Butterfly Relaxation Method -- 3.4 Theoretical Properties -- 3.4.1 Convergence -- 3.4.2 Existence of Lagrange Multipliers for the Relaxed Sub-Problems -- 3.4.3 Convergence of the Epsilon-Stationary Points -- 3.5 Numerical Results -- 3.5.1 On the Implementation of the Butterfly Relaxation -- 3.5.2 Comparison of the Relaxation Methods -- 3.6 Concluding Remarks -- Appendix -- 3.7 Proof of a Technical Lemma "]
[{"$nulls":4},"-- References -- 4 Copositive Optimization and Its Applications in Graph Theory -- 4.1 Introduction -- 4.1.1 Quadratic Programming Problem with Binary and Continuous Variables -- 4.1.2 Fractional Quadratic Optimization Problem -- 4.1.3 More on Nonconvex Quadratic Programming Problems -- 4.1.4 Quadratic Optimization Problem and the Concept of Lifted Problem -- 4.1.5 Quadratic Optimization Problem and the Role of Special Matrix Classes -- 4.2 Applications of Copositive Optimization in Graph Theory -- 4.2.1 Maximum Weight Clique Problem."]
[{"$nulls":4},"4.3 The Notion of Transfinite Diameter in a Finite Metric Space and Copositive Optimization Problem -- 4.4 Symmetric Bimatrix Game as a Copositive Optimization Problem -- References -- 5 Hermite-Hadamard Type Inequalities For Functions Whose Derivatives Are Strongly η-Convex Via Fractional Integrals -- 5.1 Introduction -- 5.2 Preliminaries -- 5.3 Main Results -- 5.3.1 Application to Means -- 5.4 Conclusion -- References -- 6 Set Order Relations, Set Optimization, and Ekeland's Variational Principle -- 6.1 Introduction -- 6.2 Preliminaries -- 6.3 Set Order Relations -- 6.3.1 Set Order Relations in Terms of the Minkowski Difference -- 6.3.2 Set Order Relations with Respect to Variable Domination Structures -- 6.4 Nonlinear Scalarization Functions -- 6.4.1 Weighted Set Order Relations -- 6.5 Solution Concepts in Set Optimization -- 6.5.1 Solution Concepts in Set Optimization with Respect to Variable Domination Structures -- 6.6 Existence of Solutions -- 6.6.1 Generalized Semicontinuity for Set-Valued Maps -- 6.6.2 Existence of Solutions in Set Optimization Problems -- 6.6.3 Relation Between Minimal Solutions with Respect to Vector and Set Approach -- 6.7 Ekeland's Variational Principle for Set-Valued Maps -- 6.7.1 A Minimal Element Theorem and Ekeland's Principle with Mixed Set Order Relations -- 6.7.2 Ekeland's Variational Principle for Set-Valued Maps in Quasi-Metric Spaces -- References -- 7 Characterizations and Generating Efficient Solutions to Interval Optimization Problems -- 7.1 Introduction -- 7.1.1 Literature Survey -- 7.1.2 Motivation and Contribution -- 7.1.3 Organization -- 7.2 Preliminaries -- 7.2.1 Interval Arithmetic -- 7.2.2 Interval-Valued Functions and Interval Optimization Problems -- 7.3 Characterizations of Efficient Solutions -- 7.3.1 Bi-objective Characterization -- 7.3.2 Saddle Point Characterization."]
[{"$nulls":4},"7.4 Generating the Complete Efficient Solution Set of IOPs -- 7.5 Conclusion -- References -- 8 Unconstrained Reformulation of Sequential Quadratic Programming and Its Application in Convex Optimization -- 8.1 Introduction -- 8.2 Mathematical Backgrounds -- 8.3 Unconstrained Reformulation of the Convex Programming -- 8.4 Geometrical Illustration -- 8.5 Numerical Examples -- 8.6 Conclusion -- References -- 9 A Note on Quadratic Penalties for Linear Ill-Posed Problems: From Tikhonov Regularization to Mollification -- 9.1 Introduction -- 9.2 Generalizing Tikhonov Regularization -- 9.3 Target Objects -- 9.4 Conclusion -- References -- 10 A New Regularization Method for Linear Exponentially Ill-Posed Problems -- 10.1 Introduction -- 10.2 The New Regularization Method -- 10.3 Optimality Results -- 10.3.1 Optimality Under Logarithmic Source Conditions -- 10.3.2 Optimality Under General Source Conditions -- 10.4 A Framework for Comparison -- 10.4.1 Computation of the Regularized Solution xα,nrmδ -- 10.4.2 Tikhonov Versus New Method -- 10.4.3 Spectral Cut-Off Versus New Method -- 10.4.4 Showalter Versus New Method -- 10.4.5 Conjugate Gradient Versus New Method -- 10.5 Numerical Illustration -- 10.6 Parameter Selection Rules -- 10.7 Conclusion -- 10.8 Appendix -- References -- 11 On Minimax Programming with Vanishing Constraints -- 11.1 Introduction -- 11.2 "]
[{"$nulls":4},"Optimality Conditions -- 11.3 Duality Results -- 11.4 Applications to Multiobjective Optimization -- 11.5 Conclusions -- References -- 12 On Minty Variational Principle  for Nonsmooth Interval-Valued Multiobjective Programming Problems -- 12.1 Introduction -- 12.1.1 The Proposed Work -- 12.2 Definition and Preliminaries -- 12.3 Relationship Among (NIVMPP), (ASVI) and (AMVI) -- 12.4 Conclusions -- References."]
[{"$nulls":4},"13 On Constraint Qualifications for Multiobjective Optimization Problems with Switching Constraints -- 13.1 Introduction -- 13.2 Preliminaries -- 13.3 Constraint Qualifications for Multiobjective Optimization Problems with Switching Constraint -- 13.3.1 A Generalized Guignard and Abadie CQ for MOPSC -- 13.4 Stationary Conditions for MOPSC -- 13.5 Sufficient Optimality Conditions for the MOPSC -- 13.6 Duality -- 13.7 Future Research Work -- References -- 14 Optimization of Physico-Chemical Parameters for the Production  of Endoxylanase Using Combined Response Surface Method and Genetic Algorithm -- 14.1 Introduction -- 14.2 Materials and Methods -- 14.2.1 Microorganism and Material -- 14.2.2 Inoculum Development for Endoxylanase Production -- 14.2.3 Production Medium -- 14.2.4 Substrate and Solid-State Fermentation -- 14.2.5 Enzyme Extraction and Assay -- 14.2.6 Experimental Design -- 14.2.7 Statistical Analysis -- 14.2.8 Genetic Algorithm -- 14.3 Results and Discussion -- 14.4 Conclusion -- References -- 15 Optimal Duration of Integrated Segment Specific and Mass Promotion Activities for Durable Technology Products: A Differential Evolution Approach -- 15.1 Introduction -- 15.2 Literature Review -- 15.2.1 Literature Gap and Research Motivation -- 15.3 Conceptual Framework and Model Development -- 15.3.1 System of Notations -- 15.3.2 Model Development -- 15.4 Solution Methodology -- 15.5 Case Study -- 15.5.1 Data Description -- 15.6 Results and Discussions -- 15.7 Managerial and Theoretical Implications -- 15.8 Conclusion and Future Scope -- References -- 16 A Secure RGB Image Encryption Algorithm in Optimized Virtual Planet Domain -- 16.1 Introduction -- 16.2 Optimized 4D Hyper-chaotic System and Virtual Planet Domain -- 16.2.1 4D Hyper-chaotic System -- 16.2.2 Teaching-learning-Based Optimization (TLBO) Algorithm."]
[{"$nulls":4},"16.2.3 Virtual Planet Domain Encoding Process -- 16.2.4 Virtual Planet Domain Encoding Process -- 16.3 Proposed Encryption and Decryption Algorithm -- 16.3.1 Encryption Procedure -- 16.3.2 Decryption Procedure -- 16.4 Statistical Analysis -- 16.4.1 Mean Square Error -- 16.4.2 Peak Signal-to-Noise Ratio -- 16.4.3 Histogram Analysis -- 16.4.4 Correlation Analysis -- 16.4.5 Cropping Analysis -- 16.4.6 Pixel Sensitivity and Key Sensitivity -- 16.4.7 Robustness Against Known Plain-Image and Chosen Cipher-Image Attacks -- 16.4.8 Differential Analysis -- 16.4.9 Information Entropy -- 16.4.10 Efficiency of Proposed Encoding Technique -- 16.4.11 Run Time of the Algorithm -- 16.5 Comparison -- 16.6 Conclusion -- References -- 17 Identification and Analysis of Key Sustainable Criteria for Third Party Reverse Logistics Provider Selection Using the Best Worst Method -- 17.1 Introduction -- 17.2 Literature Review -- 17.2.1 Outsourcing in Reverse Logistics -- 17.2.2 Sustainable Performance Criteria for Provider Selection in Reverse Logistics -- 17.2.3 Research Contribution -- 17.3 Methodology used for Selection and Evaluation  of Criteria -- 17.3.1 Identification of Criteria -- 17.3.2 Delphi Technique for Identification of Key Sustainable Criteria for 3PRLP Evaluation -- 17.3.3 Best Worst Method for Ranking of Key Sustainable Criteria for 3PRLP Evaluation -- 17.4 Application of the Proposed Methodology -- 17.4.1 Identification of Key Criteria Using Delphi Technique -- 17.4.2 Evaluation of Key Sustainable Criteria Using Best Worst Method -- 17.5 "]
[{"$nulls":4},"Result Discussion -- 17.6 Conclusion -- References -- 18 Efficiency Assessment Through Peer Evaluation and Benchmarking: A Case Study of a Retail Chain Using DEA -- 18.1 Introduction -- 18.2 Literature Review -- 18.2.1 Contribution of the Study -- 18.3 Problem Definition -- 18.4 Methodology."]
[{"$nulls":4},"18.4.1 Cross-Efficiency Assessment."]