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From Agriscience to Agribusiness : Theories, Policies and Practices in Technology Transfer and Commercialization / / edited by Nicholas Kalaitzandonakes, Elias G. Carayannis, Evangelos Grigoroudis, Stelios Rozakis
| From Agriscience to Agribusiness : Theories, Policies and Practices in Technology Transfer and Commercialization / / edited by Nicholas Kalaitzandonakes, Elias G. Carayannis, Evangelos Grigoroudis, Stelios Rozakis |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (XXVI, 491 p. 81 illus., 64 illus. in color.) |
| Disciplina | 338.16 |
| Collana | Innovation, Technology, and Knowledge Management |
| Soggetto topico |
Management
Industrial management Agricultural economics Economic policy Innovation/Technology Management Agricultural Economics R & D/Technology Policy |
| ISBN | 3-319-67958-9 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1: Introduction -- Part I: R&D Spending and Agricultural Innovation – Organization and Emerging Trends -- Chapter 2: The Shifting Structure of Agricultural R&D: Worldwide Investment Patterns and Payoffs -- Chapter 3: Private Sector Research and Development -- Chapter 4: Structural Change and Innovation in the Global Agricultural Input Sector -- Chapter 5: Private-Public R&D in the Development of the Canola Industry in Canada -- Part II: Institutional Incentives for Agricultural Innovation -- Chapter 6: Why do US Corn Yields Increase? The Contributions of Genetics, Agronomy, and Policy Instruments -- Chapter 7: Whither the Research Anticommons? -- Chapter 8: Patent Characteristics and Patent Ownership in Agricultural Biotechnology -- Chapter 9: Innovation and Technology Transfer among Firms in the Agricultural Input Sector -- Chapter 10: Land-grant University Research as a Driver of Progress in Agriscience -- Chapter 11: Agriscience Innovation at Land-grant Universities, Measured by Patents and Plant Variety Protection Certificates as Proxies -- Part III: Technology Transfer from the Public to the Private Sector -- Chapter 12: Transfer and Licensing of University Research and Technology in Canadian Agriculture -- Chapter 13: Technology Transfer in Agriculture: The Case of Wageningen University -- Chapter 14: The Evaluation Process of Research Commercialization Proposals and its Links to University Technology Transfer Strategy: A Case Study -- Chapter 15: The Technology Cycle and Technology Transfer Strategies -- Part IV: Technology Transfer to Agricultural Producers -- Chapter 16: The Role of Extension in Agricultural Technology Transfer: A Critical Review -- Chapter 17: Technology Adoption by Agricultural Producers: A Review of the Literature -- Chapter 18: Commercialization Mechanisms for New Plant Varieties -- Chapter 19: Water Efficient Maize for Africa: A Public-Private Partnership in Technology Transfer to Smallholder Farmers in Sub-Saharan Africa -- Part V: Benefits from Agricultural Research and Innovation -- Chapter 20: Public Research and Technology Transfer in US Agriculture: The Role of USDA -- Chapter 21: The Role and Impact of Public Research and Technology Transfer in Brazilian Agriculture -- Chapter 22:Public Agricultural Research and its Contributions to Agricultural Productivity -- Chapter 23: A Bayesian Measure of Research Productivity -- Chapter 24: Innovation and Technology Transfer in Agriculture: Concluding Comments. |
| Record Nr. | UNINA-9910298186903321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Multicriteria decision aid and artificial intelligence [[electronic resource] ] : links, theory and applications / / edited by Michael Doumpos and Evangelos Grigoroudis
| Multicriteria decision aid and artificial intelligence [[electronic resource] ] : links, theory and applications / / edited by Michael Doumpos and Evangelos Grigoroudis |
| Autore | Doumpos Michael |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley-Blackwell, 2013 |
| Descrizione fisica | 1 online resource (369 p.) |
| Disciplina | 658.4/033 |
| Altri autori (Persone) | GrigoroudisEvangelos |
| Soggetto topico |
Multiple criteria decision making
Artificial intelligence |
| ISBN |
1-118-52251-6
1-299-15953-2 1-118-52250-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Machine generated contents note: List of Contributors Preface Part One The Contributions of Intelligent Techniques in Multicriteria Decision Aiding 1 Computational Intelligence Techniques for Multicriteria Decision Aiding: An Overview 1.1 Introduction 1.2 The MCDA Paradigm 1.2.1 Modeling Process 1.2.2 Methodological Approaches 1.3 Computational Intelligence in MCDA 1.3.1 Statistical Learning and Data Mining 1.3.2 Fuzzy Modeling 1.3.3 Metaheuristics 1.4 Conclusions References 2 Intelligent Decision Support Systems 2.1 Introduction 2.2 Fundamentals of Human Decision Making 2.3 Decision Support System 2.4 Intelligent Decision Support Systems 2.4.1 Artificial Neural Networks for Intelligent Decision Support 2.4.2 Fuzzy Logic for Intelligent Decision Support 2.4.3 Expert Systems for Intelligent Decision Support 2.4.4 Evolutionary Computing for Intelligent Decision Support 2.4.5 Intelligent Agents for Intelligent Decision Support 2.5 Evaluating Intelligent Decision Support Systems 2.5.1 Determining Evaluation Criteria 2.5.2 Multi-Criteria Model for IDSS Assessment 2.6 Summary and Future Trends References Part Two Intelligent Technologies for Decision Support and Preference Modeling 3 Designing Distributed Multi-Criteria Decision Support Systems for Complex and Uncertain Situations 3.1 Introduction 3.2 Example Applications 3.3 Key Challenges 3.4 Making Trade-offs: Multi-criteria Decision Analysis 3.4.1 Multi-attribute Decision Support 3.4.2 Making Trade-offs Under Uncertainty 3.5 Exploring the Future: Scenario-based Reasoning 3.6 Making Robust Decisions: Combining MCDA and SBR 3.6.1 Decisions Under Uncertainty: The Concept of Robustness 3.6.2 Combining Scenarios and MCDA 3.6.3 Collecting, Sharing and Processing Information: A Distributed Approach 3.6.4 Keeping Track of Future Developments: Constructing Comparable Scenarios 3.6.5 Respecting Constraints and Requirements: Scenario Management 3.6.6 Assisting Evaluation: Assessing Large Numbers of Scenarios 3.7 Discussion 3.8 Conclusion References 4 Preference Representation with Ontologies 4.1 Introduction 4.1.1 Structure of the Chapter 4.2 Ontology-based Preference Models 4.3 Maintaining the User's Profile up to Date 4.4 Decision Making Methods Exploiting the Preference Information Stored in Ontologies 4.4.1 Recommendation Based on Aggregation 4.4.2 Recommendation Based on Similarities 4.4.3 Recommendation Based on Rules 4.5 Discussion and Open Questions References Part Three Decision Models 5 Neural Networks in Multicriteria Decision Support 5.1 Introduction 5.2 Basic Concepts of Neural Networks 5.2.1 Neural Networks for Intelligent Decision Support 5.3 Basics in Multicriteria Decision Aid 5.3.1 MCDM Problems 5.3.2 Solutions of MCDM Problems 5.4 Neural Networks and Multicriteria Decision Support 5.4.1 Review of Neural Network Applications to MCDM Problems 5.4.2 Discussion 5.5 Summary and Conclusions References 6 Rule-Based Approach to Multicriteria Ranking 6.1 Introduction 6.2 Problem Setting 6.3 Pairwise Comparison Table (PCT) 6.4 Rough Approximation of Outranking and Non-outranking Relations 6.5 Induction and Application of Decision Rules 6.6 Exploitation of Preference Graphs 6.7 Illustrative Example 6.8 Summary and Conclusions References 7 About the Application of Evidence Theory in MultiCriteria Decision Aid 7.1 Introduction 7.2 Evidence Theory: Some Concepts 7.2.1 Knowledge Model 7.2.2 Combination 7.2.3 Decision Making 7.3 New Concepts in Evidence Theory for MCDA 7.3.1 First Belief Dominance 7.3.2 RBBD Concept 7.4 Multicriteria Methods modeled by Evidence Theory 7.4.1 Evidential Reasoning Approach 7.4.2 DS/AHP 7.4.3 DISSET 7.4.4 A Choice Model Inspired by ELECTRE I 7.4.5 A Ranking Model Inspired by Xu et al.'s Method 7.5 Discussion 7.6 Conclusion References Part Four Multiobjective Optimization 8 Interactive Approaches Applied to Multiobjective Evolutionary Algorithms 8.1 Introduction 8.1.1 Methods Analyzed in this Chapter 8.2 Basic Concepts and Notation 8.2.1 Multiobjective Optimization Problems 8.2.2 Classical Interactive Methods 8.3 MOEAs Based on Reference Point Methods 8.3.1 A Weighted Distance Metric 8.3.2 Light Beam Search Combined with NSGA-II 8.3.3 Controlling the Accuracy of the Pareto Front Approximation 8.3.4 Light Beam Search Combined with PSO 8.3.5 A Preference Relation Based on a Weighted Distance Metric 8.3.6 The Chebyshev Preference Relation 8.4 MOEAs Based on Value Function Methods 8.4.1 Progressive Approximation of a Value Function 8.4.2 Value Function by Ordinal Regression 8.5 Miscellaneous Methods 8.5.1 Desirability Functions 8.6 Conclusions and Future Work References 9 Generalized DEA and Computational Intelligence in Multiple Criteria Decision Making 9.1 Introduction 9.2 Generalized Data Envelopment Analysis 9.2.1 Basic DEA Models: CCR, BCC and FDH Models 9.2.2 GDEA Model 9.3 Generation of Pareto Optimal Solutions using Generalized DEA and Computational Intelligence 9.3.1 GDEA in Fitness Evaluation 9.3.2 GDEA in Deciding the Parameters of Multi-objective PSO 9.3.3 Expected Improvement for Multi-objective Optimization Using GDEA 9.4 Summary References 10 Fuzzy Multiobjective Optimization 10.1 Introduction 10.2 Solution Concepts for Multiobjective Programming 10.3 Interactive Multiobjective Linear Programming 10.4 Fuzzy Multiobjective Linear Programming 10.5 Interactive Fuzzy Multiobjective Linear Programming 10.6 Interactive Fuzzy Multiobjective Linear Programming with Fuzzy Parameters 10.7 Interactive Fuzzy Stochastic Multiobjective Linear Programming 10.8 Related Works and Applications References Part Five Applications in Management and Engineering 11 MCDA & Agents: Supporting Effective Resource Federation in Virtual Organizations 11.1 Introduction 11.2 The Intuition of Multiple Criteria Decision Aid in Multi-agent Systems 11.3 Resource Federation Applied 11.3.1 Describing the Problem in a Cloud Computing Context 11.3.2 Problem Modeling 11.3.3 Assessing Agents' Value Function for Resource Federation 11.4 An Illustrative Example 11.5 Conclusions References 12 Fuzzy AHP Using Type II Fuzzy Sets: An Application to Warehouse Location Selection 12.1 Introduction 12.2 Multicriteria Selection 12.2.1 The ELECTRE (E |
| Record Nr. | UNINA-9910141473803321 |
Doumpos Michael
|
||
| Hoboken, N.J., : Wiley-Blackwell, 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Multicriteria decision aid and artificial intelligence : links, theory and applications / / edited by Michael Doumpos and Evangelos Grigoroudis
| Multicriteria decision aid and artificial intelligence : links, theory and applications / / edited by Michael Doumpos and Evangelos Grigoroudis |
| Autore | Doumpos Michael |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley-Blackwell, 2013 |
| Descrizione fisica | 1 online resource (369 p.) |
| Disciplina | 658.4/033 |
| Altri autori (Persone) | GrigoroudisEvangelos |
| Soggetto topico |
Multiple criteria decision making
Artificial intelligence |
| ISBN |
1-118-52251-6
1-299-15953-2 1-118-52250-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Machine generated contents note: List of Contributors Preface Part One The Contributions of Intelligent Techniques in Multicriteria Decision Aiding 1 Computational Intelligence Techniques for Multicriteria Decision Aiding: An Overview 1.1 Introduction 1.2 The MCDA Paradigm 1.2.1 Modeling Process 1.2.2 Methodological Approaches 1.3 Computational Intelligence in MCDA 1.3.1 Statistical Learning and Data Mining 1.3.2 Fuzzy Modeling 1.3.3 Metaheuristics 1.4 Conclusions References 2 Intelligent Decision Support Systems 2.1 Introduction 2.2 Fundamentals of Human Decision Making 2.3 Decision Support System 2.4 Intelligent Decision Support Systems 2.4.1 Artificial Neural Networks for Intelligent Decision Support 2.4.2 Fuzzy Logic for Intelligent Decision Support 2.4.3 Expert Systems for Intelligent Decision Support 2.4.4 Evolutionary Computing for Intelligent Decision Support 2.4.5 Intelligent Agents for Intelligent Decision Support 2.5 Evaluating Intelligent Decision Support Systems 2.5.1 Determining Evaluation Criteria 2.5.2 Multi-Criteria Model for IDSS Assessment 2.6 Summary and Future Trends References Part Two Intelligent Technologies for Decision Support and Preference Modeling 3 Designing Distributed Multi-Criteria Decision Support Systems for Complex and Uncertain Situations 3.1 Introduction 3.2 Example Applications 3.3 Key Challenges 3.4 Making Trade-offs: Multi-criteria Decision Analysis 3.4.1 Multi-attribute Decision Support 3.4.2 Making Trade-offs Under Uncertainty 3.5 Exploring the Future: Scenario-based Reasoning 3.6 Making Robust Decisions: Combining MCDA and SBR 3.6.1 Decisions Under Uncertainty: The Concept of Robustness 3.6.2 Combining Scenarios and MCDA 3.6.3 Collecting, Sharing and Processing Information: A Distributed Approach 3.6.4 Keeping Track of Future Developments: Constructing Comparable Scenarios 3.6.5 Respecting Constraints and Requirements: Scenario Management 3.6.6 Assisting Evaluation: Assessing Large Numbers of Scenarios 3.7 Discussion 3.8 Conclusion References 4 Preference Representation with Ontologies 4.1 Introduction 4.1.1 Structure of the Chapter 4.2 Ontology-based Preference Models 4.3 Maintaining the User's Profile up to Date 4.4 Decision Making Methods Exploiting the Preference Information Stored in Ontologies 4.4.1 Recommendation Based on Aggregation 4.4.2 Recommendation Based on Similarities 4.4.3 Recommendation Based on Rules 4.5 Discussion and Open Questions References Part Three Decision Models 5 Neural Networks in Multicriteria Decision Support 5.1 Introduction 5.2 Basic Concepts of Neural Networks 5.2.1 Neural Networks for Intelligent Decision Support 5.3 Basics in Multicriteria Decision Aid 5.3.1 MCDM Problems 5.3.2 Solutions of MCDM Problems 5.4 Neural Networks and Multicriteria Decision Support 5.4.1 Review of Neural Network Applications to MCDM Problems 5.4.2 Discussion 5.5 Summary and Conclusions References 6 Rule-Based Approach to Multicriteria Ranking 6.1 Introduction 6.2 Problem Setting 6.3 Pairwise Comparison Table (PCT) 6.4 Rough Approximation of Outranking and Non-outranking Relations 6.5 Induction and Application of Decision Rules 6.6 Exploitation of Preference Graphs 6.7 Illustrative Example 6.8 Summary and Conclusions References 7 About the Application of Evidence Theory in MultiCriteria Decision Aid 7.1 Introduction 7.2 Evidence Theory: Some Concepts 7.2.1 Knowledge Model 7.2.2 Combination 7.2.3 Decision Making 7.3 New Concepts in Evidence Theory for MCDA 7.3.1 First Belief Dominance 7.3.2 RBBD Concept 7.4 Multicriteria Methods modeled by Evidence Theory 7.4.1 Evidential Reasoning Approach 7.4.2 DS/AHP 7.4.3 DISSET 7.4.4 A Choice Model Inspired by ELECTRE I 7.4.5 A Ranking Model Inspired by Xu et al.'s Method 7.5 Discussion 7.6 Conclusion References Part Four Multiobjective Optimization 8 Interactive Approaches Applied to Multiobjective Evolutionary Algorithms 8.1 Introduction 8.1.1 Methods Analyzed in this Chapter 8.2 Basic Concepts and Notation 8.2.1 Multiobjective Optimization Problems 8.2.2 Classical Interactive Methods 8.3 MOEAs Based on Reference Point Methods 8.3.1 A Weighted Distance Metric 8.3.2 Light Beam Search Combined with NSGA-II 8.3.3 Controlling the Accuracy of the Pareto Front Approximation 8.3.4 Light Beam Search Combined with PSO 8.3.5 A Preference Relation Based on a Weighted Distance Metric 8.3.6 The Chebyshev Preference Relation 8.4 MOEAs Based on Value Function Methods 8.4.1 Progressive Approximation of a Value Function 8.4.2 Value Function by Ordinal Regression 8.5 Miscellaneous Methods 8.5.1 Desirability Functions 8.6 Conclusions and Future Work References 9 Generalized DEA and Computational Intelligence in Multiple Criteria Decision Making 9.1 Introduction 9.2 Generalized Data Envelopment Analysis 9.2.1 Basic DEA Models: CCR, BCC and FDH Models 9.2.2 GDEA Model 9.3 Generation of Pareto Optimal Solutions using Generalized DEA and Computational Intelligence 9.3.1 GDEA in Fitness Evaluation 9.3.2 GDEA in Deciding the Parameters of Multi-objective PSO 9.3.3 Expected Improvement for Multi-objective Optimization Using GDEA 9.4 Summary References 10 Fuzzy Multiobjective Optimization 10.1 Introduction 10.2 Solution Concepts for Multiobjective Programming 10.3 Interactive Multiobjective Linear Programming 10.4 Fuzzy Multiobjective Linear Programming 10.5 Interactive Fuzzy Multiobjective Linear Programming 10.6 Interactive Fuzzy Multiobjective Linear Programming with Fuzzy Parameters 10.7 Interactive Fuzzy Stochastic Multiobjective Linear Programming 10.8 Related Works and Applications References Part Five Applications in Management and Engineering 11 MCDA & Agents: Supporting Effective Resource Federation in Virtual Organizations 11.1 Introduction 11.2 The Intuition of Multiple Criteria Decision Aid in Multi-agent Systems 11.3 Resource Federation Applied 11.3.1 Describing the Problem in a Cloud Computing Context 11.3.2 Problem Modeling 11.3.3 Assessing Agents' Value Function for Resource Federation 11.4 An Illustrative Example 11.5 Conclusions References 12 Fuzzy AHP Using Type II Fuzzy Sets: An Application to Warehouse Location Selection 12.1 Introduction 12.2 Multicriteria Selection 12.2.1 The ELECTRE (E |
| Record Nr. | UNINA-9910812188803321 |
|
Doumpos Michael
|
||
| Hoboken, N.J., : Wiley-Blackwell, 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Operational Research in Business and Economics : 4th International Symposium and 26th National Conference on Operational Research, Chania, Greece, June 2015 / / edited by Evangelos Grigoroudis, Michael Doumpos
| Operational Research in Business and Economics : 4th International Symposium and 26th National Conference on Operational Research, Chania, Greece, June 2015 / / edited by Evangelos Grigoroudis, Michael Doumpos |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (XIII, 284 p. 53 illus., 35 illus. in color.) |
| Disciplina | 658.4034 |
| Collana | Springer Proceedings in Business and Economics |
| Soggetto topico |
Operations research
Decision making Management science Operations Research/Decision Theory Operations Research, Management Science |
| ISBN | 3-319-33003-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | The application of a business process modeling architecture in the supply chain of a manufacturing company: A case study -- How Environmental Knowledge of Managers Plays a Critical Role in Implementing Green Supply Chain Management -- Retail Category Management: A review on assortment and shelf-space planning models -- Cultural and creative industries innovation strategies for New Service Development using MCDA -- Fostering a competitive differentiation strategy for sustainable organizational performance -- Decision aiding process in the frame of the strategic farm management -- Exploring population drift on consumer credit behavioral scoring -- Solving Portfolio Optimization Problems using AMPL -- Approximating throughput of small production lines using genetic programming -- An Island Memetic Algorithm for Real World Vehicle Routing Problems -- Three-dimensional multiple-bin-size bin packing: A case study with a new MILP-based upper bound -- The effects of quality on market share and profitability in single stage make-to-stock production systems -- Two-warehouse inventory systems for seasonal deteriorating products with permissible delay in payments -- Optimal Active Power Management in All Electric Ship employing DC Grid technology. . |
| Record Nr. | UNINA-9910254919703321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Preference Disaggregation in Multiple Criteria Decision Analysis : Essays in Honor of Yannis Siskos / / edited by Nikolaos Matsatsinis, Evangelos Grigoroudis
| Preference Disaggregation in Multiple Criteria Decision Analysis : Essays in Honor of Yannis Siskos / / edited by Nikolaos Matsatsinis, Evangelos Grigoroudis |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (XIX, 235 p. 68 illus., 5 illus. in color.) |
| Disciplina | 658.40301 |
| Collana | Multiple Criteria Decision Making |
| Soggetto topico |
Operations research
Decision making Management science Operations Research/Decision Theory Operations Research, Management Science |
| ISBN | 3-319-90599-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | What Is a Decision Problem? Designing Alternatives -- MCDA Approaches for Efficient Strategic Decision Making -- Collaborative Decision Making for Small Groups utilizing UTA Methods -- Disaggregation Approaches for Multicriteria Classification: An Overview -- Multiple Criteria Approaches for Customer Satisfaction Measurement -- Projects Portfolio Selection Framework Combining MCDA UTASTAR Method with 0-1 Multi-Objective Programming -- Applying the Disaggregation-Aggregation Paradigm for Crude Oil Pipeline Risk Management -- International Cooperation for Clean Electricity: A UTASTAR Application in Energy Policy -- Developing Regional Strategies Based on Tourist Behaviour Analysis: A multiple Criteria Approach -- Analyzing Perceived Quality of Health Care Services: A Multicriteria Decision Analysis Approach Based on the Theory of Attractive Quality. . |
| Record Nr. | UNINA-9910298188603321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Robustness analysis in decision aiding, optimization, and analytics / / edited by Michael Doumpos, Constantin Zopounidis, Evangelos Grigoroudis
| Robustness analysis in decision aiding, optimization, and analytics / / edited by Michael Doumpos, Constantin Zopounidis, Evangelos Grigoroudis |
| Edizione | [1st ed. 2016.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
| Descrizione fisica | 1 online resource (XXI, 321 p. 65 illus., 27 illus. in color.) |
| Disciplina | 658.4033 |
| Collana | International Series in Operations Research & Management Science |
| Soggetto topico |
Operations research
Decision making Management science Operations Research/Decision Theory Operations Research, Management Science |
| ISBN | 3-319-33121-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | SMAA in Robustness Analysis -- Data-driven Robustness Analysis for Multicriteria Classification Problems Using Preference Disaggregation Approaches -- Robustness for Adversarial Risk Analysis -- From Statistical Decision Theory to Robust Optimization: A Maximin Perspective on Robust Decision-Making -- The State of Robust Optimization -- Robust Discrete Optimization under Discrete and Interval Uncertainty - A Survey -- Performance Analysis in Robust Optimization -- Robust-Soft Solutions in Linear Optimization Problems with Fuzzy Parameters -- Robust Machine Scheduling Based on Group of Permutable Jobs -- How Robust is a Robust Policy? Comparing Alternative Robustness Metrics for Robust Decision-making -- Developing Robust Climate Policies: A Fuzzy Cognitive Map Approach -- Robust Optimization Approaches to Single Period Portfolio Allocation Problem -- Portfolio Optimization with Second-Order Stochastic Dominance Constraints and Portfolios Dominating Indices -- Robust DEA Approaches to Performance Evaluation of Olive Oil Production under Uncertainty. . |
| Record Nr. | UNINA-9910254950303321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||