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Artificial Evolution [[electronic resource] ] : 14th International Conference, Évolution Artificielle, EA 2019, Mulhouse, France, October 29–30, 2019, Revised Selected Papers / / edited by Lhassane Idoumghar, Pierrick Legrand, Arnaud Liefooghe, Evelyne Lutton, Nicolas Monmarché, Marc Schoenauer
| Artificial Evolution [[electronic resource] ] : 14th International Conference, Évolution Artificielle, EA 2019, Mulhouse, France, October 29–30, 2019, Revised Selected Papers / / edited by Lhassane Idoumghar, Pierrick Legrand, Arnaud Liefooghe, Evelyne Lutton, Nicolas Monmarché, Marc Schoenauer |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (xiv, 218 pages) : illustrations |
| Disciplina | 006.3 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Artificial intelligence
Algorithms Numerical analysis Computer networks Computer engineering Artificial Intelligence Numerical Analysis Computer Communication Networks Computer Engineering and Networks |
| ISBN | 3-030-45715-X |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | From Feature Selection to Continuous Optimization -- Evolving a Weighted Combination of Text Similarities for Authorship Attribution -- Image Signal Processor Parameter Tuning with Surrogate-assisted Particle Swarm Optimization -- Combinatorial Surrogate-assisted Optimization for Bus Stops Spacing Problem -- Optimization of a Checkers Player Using Neural and Metaheuristic Approaches -- A Novel Outlook on Feature Selection as a Multi-Objective Problem -- Fast Evolutionary Algorithm for Solving Large-scale Multi-objective Problems -- Looking for Energy Efficient Genetic Algorithms -- Evolving Fitness Landscapes with Complementary Fitness Functions -- Bayesian Immigrant Diploid Genetic Algorithm for Dynamic Environments -- Ant Colony Optimization Algorithm for a Transportation Problem in Home Health Care with the Consideration of Carbon Emissions -- Selective Vehicle Routing Problem: A Hybrid Genetic Algorithm Approach -- Fixed Jobs Multi-agent Scheduling Problem with Renewable Resources -- A Study of Recombination Operators for the Cyclic Bandwidth Problem -- Automatic Calibration of a Farm Irrigation Model: a Multi-modal Optimization Approach -- A Hybrid Evolutionary Algorithm for Offline UAV Path Planning. |
| Record Nr. | UNISA-996418216103316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Artificial Evolution : 14th International Conference, Évolution Artificielle, EA 2019, Mulhouse, France, October 29–30, 2019, Revised Selected Papers / / edited by Lhassane Idoumghar, Pierrick Legrand, Arnaud Liefooghe, Evelyne Lutton, Nicolas Monmarché, Marc Schoenauer
| Artificial Evolution : 14th International Conference, Évolution Artificielle, EA 2019, Mulhouse, France, October 29–30, 2019, Revised Selected Papers / / edited by Lhassane Idoumghar, Pierrick Legrand, Arnaud Liefooghe, Evelyne Lutton, Nicolas Monmarché, Marc Schoenauer |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (xiv, 218 pages) : illustrations |
| Disciplina |
006.3
005.1 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Artificial intelligence
Algorithms Numerical analysis Computer networks Computer engineering Artificial Intelligence Numerical Analysis Computer Communication Networks Computer Engineering and Networks |
| ISBN | 3-030-45715-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | From Feature Selection to Continuous Optimization -- Evolving a Weighted Combination of Text Similarities for Authorship Attribution -- Image Signal Processor Parameter Tuning with Surrogate-assisted Particle Swarm Optimization -- Combinatorial Surrogate-assisted Optimization for Bus Stops Spacing Problem -- Optimization of a Checkers Player Using Neural and Metaheuristic Approaches -- A Novel Outlook on Feature Selection as a Multi-Objective Problem -- Fast Evolutionary Algorithm for Solving Large-scale Multi-objective Problems -- Looking for Energy Efficient Genetic Algorithms -- Evolving Fitness Landscapes with Complementary Fitness Functions -- Bayesian Immigrant Diploid Genetic Algorithm for Dynamic Environments -- Ant Colony Optimization Algorithm for a Transportation Problem in Home Health Care with the Consideration of Carbon Emissions -- Selective Vehicle Routing Problem: A Hybrid Genetic Algorithm Approach -- Fixed Jobs Multi-agent Scheduling Problem with Renewable Resources -- A Study of Recombination Operators for the Cyclic Bandwidth Problem -- Automatic Calibration of a Farm Irrigation Model: a Multi-modal Optimization Approach -- A Hybrid Evolutionary Algorithm for Offline UAV Path Planning. |
| Record Nr. | UNINA-9910409672003321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Evolutionary Computation in Combinatorial Optimization [[electronic resource] ] : 19th European Conference, EvoCOP 2019, Held as Part of EvoStar 2019, Leipzig, Germany, April 24–26, 2019, Proceedings / / edited by Arnaud Liefooghe, Luís Paquete
| Evolutionary Computation in Combinatorial Optimization [[electronic resource] ] : 19th European Conference, EvoCOP 2019, Held as Part of EvoStar 2019, Leipzig, Germany, April 24–26, 2019, Proceedings / / edited by Arnaud Liefooghe, Luís Paquete |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XIV, 213 p. 55 illus., 32 illus. in color.) |
| Disciplina | 006.3823 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Numerical analysis
Algorithms Artificial intelligence Computer science—Mathematics Discrete mathematics Artificial intelligence—Data processing Numerical Analysis Artificial Intelligence Discrete Mathematics in Computer Science Data Science |
| ISBN | 3-030-16711-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996466276003316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Evolutionary Computation in Combinatorial Optimization : 19th European Conference, EvoCOP 2019, Held as Part of EvoStar 2019, Leipzig, Germany, April 24–26, 2019, Proceedings / / edited by Arnaud Liefooghe, Luís Paquete
| Evolutionary Computation in Combinatorial Optimization : 19th European Conference, EvoCOP 2019, Held as Part of EvoStar 2019, Leipzig, Germany, April 24–26, 2019, Proceedings / / edited by Arnaud Liefooghe, Luís Paquete |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XIV, 213 p. 55 illus., 32 illus. in color.) |
| Disciplina | 006.3823 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Numerical analysis
Algorithms Artificial intelligence Computer science—Mathematics Discrete mathematics Artificial intelligence—Data processing Numerical Analysis Artificial Intelligence Discrete Mathematics in Computer Science Data Science |
| ISBN | 3-030-16711-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910337847703321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Evolutionary Computation in Combinatorial Optimization [[electronic resource] ] : 18th European Conference, EvoCOP 2018, Parma, Italy, April 4–6, 2018, Proceedings / / edited by Arnaud Liefooghe, Manuel López-Ibáñez
| Evolutionary Computation in Combinatorial Optimization [[electronic resource] ] : 18th European Conference, EvoCOP 2018, Parma, Italy, April 4–6, 2018, Proceedings / / edited by Arnaud Liefooghe, Manuel López-Ibáñez |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (XIV, 189 p. 31 illus.) |
| Disciplina | 005.432 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Numerical analysis
Algorithms Artificial intelligence Computer science—Mathematics Discrete mathematics Artificial intelligence—Data processing Numerical Analysis Artificial Intelligence Discrete Mathematics in Computer Science Data Science |
| ISBN | 3-319-77449-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Better Runtime Guarantees via Stochastic Domination -- 1 Introduction -- 2 Stochastic Domination -- 3 Domination-Based Fitness Level Method -- 4 Beyond the Fitness Level Theorem -- 5 Structural Domination -- 6 Conclusion -- References -- On the Fractal Nature of Local Optima Networks -- 1 Introduction -- 2 Background -- 2.1 The Study of Fitness Landscapes -- 2.2 The Local Optima Network -- 2.3 The Fractal Dimension -- 2.4 Fractals and Fitness Landscapes -- 2.5 Fractals and Complex Networks -- 3 Experimental Setting -- 3.1 Test Problem -- 3.2 Metaheuristics -- 3.3 Fractal Analysis -- 4 Results -- 4.1 Fractals and Epistasis -- 4.2 Fractal Dimension and Search Performance -- 5 Discussion -- 5.1 The Fractal Shape of Local Optima Networks -- 5.2 Connections with Search Difficulty -- 6 Conclusions and Future Work -- References -- How Perturbation Strength Shapes the Global Structure of TSP Fitness Landscapes -- 1 Introduction -- 2 Definitions and Algorithms -- 3 Empirical Methodology -- 3.1 Instances -- 3.2 Sampling Method -- 3.3 Performance and Network Metrics -- 4 Results and Analysis -- 4.1 Visualisation -- 4.2 Performance and Network Metrics Results -- 4.3 Impact of Perturbation Strength on Success Rate -- 4.4 Correlation Analysis -- 4.5 Correlation Variance Between Instance Classes -- 5 Conclusions -- References -- Worst Improvement Based Iterated Local Search -- 1 Introduction -- 2 Definitions -- 2.1 Fitness Landscapes and Related Concepts -- 2.2 Bit-String Landscapes Instances -- 3 Worst Improvement Hill-Climbing -- 3.1 Pivoting Rules -- 3.2 Additional Experiments -- 4 Experimental Analysis -- 4.1 Experimental Protocol -- 4.2 Results -- 4.3 ILS Performance and Landscape Features -- 5 Conclusion -- References.
Automatic Grammar-Based Design of Heuristic Algorithms for Unconstrained Binary Quadratic Programming -- 1 Introduction -- 2 Related Work -- 3 Proposed Approach -- 3.1 Grammar and the Heuristic Search Space -- 3.2 Automatic Design Using irace -- 4 Experiments and Results -- 4.1 Tuning with a Single Instance Set -- 4.2 Tuning with a Random Instance Set -- 5 Conclusions -- References -- Automatic Algorithm Configuration for the Permutation Flow Shop Scheduling Problem Minimizing Total Completion Time -- 1 Introduction -- 2 Automatic Algorithm Configuration -- 2.1 Grammar and Components -- 2.2 Solution Representation -- 2.3 Search Strategy -- 3 Computational Experiments -- 3.1 Benchmarks -- 3.2 Experimental Setup -- 3.3 Results -- 4 Conclusions -- References -- Data Clustering Using Grouping Hyper-heuristics -- 1 Introduction -- 2 Related Work -- 2.1 Solution Representation in Grouping Problems -- 2.2 Data Clustering -- 3 A Grouping Hyper-heuristic Approach to Solve Grouping Problems -- 3.1 Low Level Heuristics -- 3.2 Selection Hyper-heuristic Components -- 4 Application of Grouping Hyper-heuristics to Data Clustering -- 4.1 Experimental Data -- 4.2 Trials and Parameters Settings and CPU Specifications -- 4.3 Evaluation Criteria -- 4.4 Experimental Results and Remarks -- 5 Conclusion -- References -- Reference Point Adaption Method -1for Genetic Programming Hyper-Heuristic in Many-Objective Job Shop Scheduling -- 1 Introduction -- 2 Background -- 2.1 Problem Description of JSS -- 2.2 Related Work -- 3 Adaptive Reference Points for Many-Objective JSS -- 3.1 Fitness Evaluation -- 3.2 Reference Point Generation -- 4 Experiment Design -- 4.1 Parameter Settings -- 4.2 Data Set -- 4.3 Performance Measures -- 5 Results and Discussions -- 5.1 Overall Result -- 6 Conclusion -- References. MOEA/DEP: An Algebraic Decomposition-Based Evolutionary Algorithm for the Multiobjective Permutation Flowshop Scheduling Problem -- 1 Introduction and Related Work -- 2 Multiobjective Optimization and MOEA/D Framework -- 3 Algebraic Differential Evolution for Permutations -- 4 MOEA/DEP -- 4.1 Initialization -- 4.2 Offsprings Generation -- 4.3 Population Update -- 4.4 Crossover for Permutations -- 5 Experiments -- 5.1 Parameters Calibration -- 5.2 Comparison with MEDA/D-MK -- 6 Conclusion and Future Work -- References -- An Evolutionary Algorithm with Practitioner's-Knowledge-Based Operators for the Inventory Routing Problem -- 1 Introduction -- 2 Problem Definition -- 3 Evolutionary Approach -- 3.1 Search Space and Solution Encoding -- 3.2 Initial Population -- 3.3 Recombination Operator -- 3.4 Date-Changing Mutation (DM) -- 3.5 Order-Changing Mutation (OM) -- 4 Experiments -- 5 Conclusions -- References -- A Multistart Alternating Tabu Search for Commercial Districting -- 1 Introduction -- 2 Definitions -- 3 Proposed Methods -- 3.1 Solution Construction -- 3.2 Optimizing Balance -- 3.3 Optimizing Compactness -- 3.4 Data Structures for Efficient Operations -- 4 Computational Experiments -- 4.1 Test Instances -- 4.2 Experimental Setup -- 4.3 Experiment 1: Constructive Algorithm -- 4.4 Experiment 2: Search Strategies -- 4.5 Experiment 3: Comparison with Existing Methods -- 5 Concluding Remarks -- References -- An Ant Colony Approach for the Winner Determination Problem -- 1 Introduction -- 1.1 Main Contributions -- 2 Winner Determination Problem -- 3 Literature Review -- 3.1 Exact Methods -- 3.2 Inexact Methods -- 4 Proposed Approach -- 4.1 Preprocessing Phase -- 4.2 Theoretical Convergence to Optimal for WDP -- 5 Randomized Pheromone Updating -- 5.1 Min-Max Pheromone Level -- 6 Randomized Graph Pruning -- 7 Experimental Results. 8 Conclusion and Future Research -- References -- Erratum to: On the Fractal Nature of Local Optima Networks -- Erratum to: Chapter "On the Fractal Nature of Local Optima Networks" in: A. Liefooghe and M. López-Ibáñez (Eds.): Evolutionary Computation in Combinatorial Optimization, LNCS 10782, https://doi.org/10.1007/978-3-319-77449-7_2 -- Author Index. |
| Record Nr. | UNISA-996465748203316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Evolutionary Computation in Combinatorial Optimization : 18th European Conference, EvoCOP 2018, Parma, Italy, April 4–6, 2018, Proceedings / / edited by Arnaud Liefooghe, Manuel López-Ibáñez
| Evolutionary Computation in Combinatorial Optimization : 18th European Conference, EvoCOP 2018, Parma, Italy, April 4–6, 2018, Proceedings / / edited by Arnaud Liefooghe, Manuel López-Ibáñez |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (XIV, 189 p. 31 illus.) |
| Disciplina | 005.432 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Numerical analysis
Algorithms Artificial intelligence Computer science—Mathematics Discrete mathematics Artificial intelligence—Data processing Numerical Analysis Artificial Intelligence Discrete Mathematics in Computer Science Data Science |
| ISBN | 3-319-77449-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Better Runtime Guarantees via Stochastic Domination -- 1 Introduction -- 2 Stochastic Domination -- 3 Domination-Based Fitness Level Method -- 4 Beyond the Fitness Level Theorem -- 5 Structural Domination -- 6 Conclusion -- References -- On the Fractal Nature of Local Optima Networks -- 1 Introduction -- 2 Background -- 2.1 The Study of Fitness Landscapes -- 2.2 The Local Optima Network -- 2.3 The Fractal Dimension -- 2.4 Fractals and Fitness Landscapes -- 2.5 Fractals and Complex Networks -- 3 Experimental Setting -- 3.1 Test Problem -- 3.2 Metaheuristics -- 3.3 Fractal Analysis -- 4 Results -- 4.1 Fractals and Epistasis -- 4.2 Fractal Dimension and Search Performance -- 5 Discussion -- 5.1 The Fractal Shape of Local Optima Networks -- 5.2 Connections with Search Difficulty -- 6 Conclusions and Future Work -- References -- How Perturbation Strength Shapes the Global Structure of TSP Fitness Landscapes -- 1 Introduction -- 2 Definitions and Algorithms -- 3 Empirical Methodology -- 3.1 Instances -- 3.2 Sampling Method -- 3.3 Performance and Network Metrics -- 4 Results and Analysis -- 4.1 Visualisation -- 4.2 Performance and Network Metrics Results -- 4.3 Impact of Perturbation Strength on Success Rate -- 4.4 Correlation Analysis -- 4.5 Correlation Variance Between Instance Classes -- 5 Conclusions -- References -- Worst Improvement Based Iterated Local Search -- 1 Introduction -- 2 Definitions -- 2.1 Fitness Landscapes and Related Concepts -- 2.2 Bit-String Landscapes Instances -- 3 Worst Improvement Hill-Climbing -- 3.1 Pivoting Rules -- 3.2 Additional Experiments -- 4 Experimental Analysis -- 4.1 Experimental Protocol -- 4.2 Results -- 4.3 ILS Performance and Landscape Features -- 5 Conclusion -- References.
Automatic Grammar-Based Design of Heuristic Algorithms for Unconstrained Binary Quadratic Programming -- 1 Introduction -- 2 Related Work -- 3 Proposed Approach -- 3.1 Grammar and the Heuristic Search Space -- 3.2 Automatic Design Using irace -- 4 Experiments and Results -- 4.1 Tuning with a Single Instance Set -- 4.2 Tuning with a Random Instance Set -- 5 Conclusions -- References -- Automatic Algorithm Configuration for the Permutation Flow Shop Scheduling Problem Minimizing Total Completion Time -- 1 Introduction -- 2 Automatic Algorithm Configuration -- 2.1 Grammar and Components -- 2.2 Solution Representation -- 2.3 Search Strategy -- 3 Computational Experiments -- 3.1 Benchmarks -- 3.2 Experimental Setup -- 3.3 Results -- 4 Conclusions -- References -- Data Clustering Using Grouping Hyper-heuristics -- 1 Introduction -- 2 Related Work -- 2.1 Solution Representation in Grouping Problems -- 2.2 Data Clustering -- 3 A Grouping Hyper-heuristic Approach to Solve Grouping Problems -- 3.1 Low Level Heuristics -- 3.2 Selection Hyper-heuristic Components -- 4 Application of Grouping Hyper-heuristics to Data Clustering -- 4.1 Experimental Data -- 4.2 Trials and Parameters Settings and CPU Specifications -- 4.3 Evaluation Criteria -- 4.4 Experimental Results and Remarks -- 5 Conclusion -- References -- Reference Point Adaption Method -1for Genetic Programming Hyper-Heuristic in Many-Objective Job Shop Scheduling -- 1 Introduction -- 2 Background -- 2.1 Problem Description of JSS -- 2.2 Related Work -- 3 Adaptive Reference Points for Many-Objective JSS -- 3.1 Fitness Evaluation -- 3.2 Reference Point Generation -- 4 Experiment Design -- 4.1 Parameter Settings -- 4.2 Data Set -- 4.3 Performance Measures -- 5 Results and Discussions -- 5.1 Overall Result -- 6 Conclusion -- References. MOEA/DEP: An Algebraic Decomposition-Based Evolutionary Algorithm for the Multiobjective Permutation Flowshop Scheduling Problem -- 1 Introduction and Related Work -- 2 Multiobjective Optimization and MOEA/D Framework -- 3 Algebraic Differential Evolution for Permutations -- 4 MOEA/DEP -- 4.1 Initialization -- 4.2 Offsprings Generation -- 4.3 Population Update -- 4.4 Crossover for Permutations -- 5 Experiments -- 5.1 Parameters Calibration -- 5.2 Comparison with MEDA/D-MK -- 6 Conclusion and Future Work -- References -- An Evolutionary Algorithm with Practitioner's-Knowledge-Based Operators for the Inventory Routing Problem -- 1 Introduction -- 2 Problem Definition -- 3 Evolutionary Approach -- 3.1 Search Space and Solution Encoding -- 3.2 Initial Population -- 3.3 Recombination Operator -- 3.4 Date-Changing Mutation (DM) -- 3.5 Order-Changing Mutation (OM) -- 4 Experiments -- 5 Conclusions -- References -- A Multistart Alternating Tabu Search for Commercial Districting -- 1 Introduction -- 2 Definitions -- 3 Proposed Methods -- 3.1 Solution Construction -- 3.2 Optimizing Balance -- 3.3 Optimizing Compactness -- 3.4 Data Structures for Efficient Operations -- 4 Computational Experiments -- 4.1 Test Instances -- 4.2 Experimental Setup -- 4.3 Experiment 1: Constructive Algorithm -- 4.4 Experiment 2: Search Strategies -- 4.5 Experiment 3: Comparison with Existing Methods -- 5 Concluding Remarks -- References -- An Ant Colony Approach for the Winner Determination Problem -- 1 Introduction -- 1.1 Main Contributions -- 2 Winner Determination Problem -- 3 Literature Review -- 3.1 Exact Methods -- 3.2 Inexact Methods -- 4 Proposed Approach -- 4.1 Preprocessing Phase -- 4.2 Theoretical Convergence to Optimal for WDP -- 5 Randomized Pheromone Updating -- 5.1 Min-Max Pheromone Level -- 6 Randomized Graph Pruning -- 7 Experimental Results. 8 Conclusion and Future Research -- References -- Erratum to: On the Fractal Nature of Local Optima Networks -- Erratum to: Chapter "On the Fractal Nature of Local Optima Networks" in: A. Liefooghe and M. López-Ibáñez (Eds.): Evolutionary Computation in Combinatorial Optimization, LNCS 10782, https://doi.org/10.1007/978-3-319-77449-7_2 -- Author Index. |
| Record Nr. | UNINA-9910349457903321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||