{"text_format":"2","workbook":"xls","n_sheets":1,"sheets":["report2"],"not_rendered":{"charts":0,"images":0,"macros":0,"external_links":1,"defined_names":3,"comments":0,"pivot_tables":0},"unopened":[],"bounds":{"document_bytes":16777216,"sheet_cells":100000,"run_cost":"one","rows_first":2000,"rows_last":500,"rows_between":2000,"halvings":0,"cell_chars":16384,"cell_head_chars":4096},"cells_cut":0,"cells_raw":0,"read":"whole","date_system":"1900","formulas":"cached_only"}

{"sheet":"report2","index":0,"n_rows":56,"n_cols":5,"rows_kept":56,"cut":false,"hidden":false,"merged":[[0,2,0,3],[0,4,0,5],[1,2,1,3],[1,4,1,5],[2,2,2,3],[3,2,3,3],[4,2,4,3],[5,2,5,3],[6,2,6,3],[7,2,7,3],[8,2,8,3],[20,2,20,3],[21,2,21,3],[24,2,24,3],[34,2,34,3],[34,4,34,5],[35,2,35,3],[35,4,35,5],[36,2,36,3],[37,2,37,3],[38,2,38,3],[39,2,39,3],[43,2,43,3],[44,2,44,3],[47,2,47,3],[47,4,47,5],[48,2,48,3],[48,4,48,5],[49,2,49,3],[50,2,50,3],[51,2,51,3],[52,2,52,3],[53,2,53,3],[54,2,54,3]],"flags":["formulas_cached_only"]}
[null,"1.","Record Nr.",null,"UNISA996465924003316"]
[null,null,"Titolo",null,"Learning and Intelligent Optimization [[electronic resource] ] : 5th International Conference, LION 5, Rome, Italy, January 17-21, 2011, Selected Papers / / edited by Carlos A. Coello-Coello"]
[null,null,"Pubbl/distr/stampa",null,"Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2011"]
[null,null,"ISBN",null,"3-642-25566-3"]
[null,null,"Edizione",null,"[1st ed. 2011.]"]
[null,null,"Descrizione fisica",null,"1 online resource (XVII, 636 p.)"]
[null,null,"Collana",null,"Theoretical Computer Science and General Issues, , 2512-2029 ; ; 6683"]
[null,null,"Disciplina",null,"006.33"]
[null,null,"Soggetti",null,"Algorithms"]
[{"$nulls":4},"Computer science"]
[{"$nulls":4},"Artificial intelligence"]
[{"$nulls":4},"Computer networks"]
[{"$nulls":4},"Pattern recognition systems"]
[{"$nulls":4},"Computer science—Mathematics"]
[{"$nulls":4},"Discrete mathematics"]
[{"$nulls":4},"Theory of Computation"]
[{"$nulls":4},"Artificial Intelligence"]
[{"$nulls":4},"Computer Communication Networks"]
[{"$nulls":4},"Automated Pattern Recognition"]
[{"$nulls":4},"Discrete Mathematics in Computer Science"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Includes index."]
[null,null,"Nota di contenuto",null,"Intro -- Title -- Preface -- Organization -- Table of Contents -- Main Track (Regular Papers) -- Multivariate Statistical Tests for Comparing  Classification Algorithms -- Introduction -- Pairwise Comparison -- Univariate Case -- Multivariate Case -- Analysis of Variance -- Univariate Case -- Multivariate Case -- Experiments -- Setup -- Results -- Conclusions -- References -- Using Hyperheuristics under a GP Framework  for Financial Forecasting -- Introduction -- Presentation of EDDIE 8 -- Hyperheuristics Framework -- Heuristics and Operators -- The Framework -- Experimental Setup -- Results -- Conclusion -- References -- On the Effect of Connectedness for  Biobjective Multiple and Long Path Problems -- Introduction -- Background -- Multiobjective Combinatorial Optimization -- Local "]
[{"$nulls":4},"Search and Connectedness -- The Single-Objective Long k-Path Problem -- The Biobjective Long k-Path Problem -- Definition -- Experimental Analysis -- The Biobjective Multiple k-Path Problem -- Definition -- Experimental Analysis -- Conclusions and Future Works -- References -- Improving Parallel Local Search for SAT -- Introduction -- Background -- The Propositional Satisfiability Problem -- Local Search for SAT -- Refinements -- Previous Work -- Complete Methods for Parallel SAT -- Incomplete Methods for Parallel SAT -- Cooperative Algorithms -- Knowledge Sharing in Parallel Local Search for SAT -- Using Best Known Configurations -- Weighting Best Known Configurations -- Restart Policy -- Experiments -- Experimental Settings -- Practical Performances with 4 Cores -- Practical Performances with 8 Cores -- Hardware Impact -- Conclusions and Future Work -- References -- Variable Neighborhood Search for the  Time-Dependent Vehicle Routing Problem with Soft Time Windows -- Introduction -- Problem Description -- Solution Method -- Initial Solution -- Shaking."]
[{"$nulls":4},"Local Search -- Acceptance Decision -- Computational Results -- Conclusion -- References -- Solving the Two-Dimensional Bin Packing  Problem with a Probabilistic Multi-start Heuristic -- Introduction -- Organization of the Paper -- Related Work -- A New ILP Model -- The Proposed Algorithm -- Probabilistic LGFi -- Multi-start Algorithm -- Experimental Evaluation -- Problem Instances -- Parameter Setting -- Computational Results -- Conclusions -- References -- Genetic Diversity and Effective Crossover in  Evolutionary Many-objective Optimization -- Introduction -- Analysis of Pareto Optimal Solutions in Many-objective 0/1 Knapsack Problem -- Mating Based on Proximity in Objective Space -- Related Works -- Local Recombination -- Controlling Crossed Genes for Crossover -- Problem of Local Recombination in MaOPs -- CCG for Two-Point Crossover (CCGTX) -- CCG for Uniform Crossover (CCGUX) -- Preparation -- Algorithms and Selection Methods -- Problems, Parameters and Metrics -- Experimental Results and Discussion -- Diversity of Genes in the Population Obtained by Conventional Crossover -- Effects of Local Recombination in MaOPs -- Effects of CCGTX in MaOPs -- Effects of CCGUX in MaOPs -- Conclusions -- References -- An Optimal Stopping Strategy for Online  Calibration in Local Search -- Introduction -- The Bruss Algorithm -- The Estimation of the Probability of Success in Local Exploration -- Illustration of the Approach -- Experiments -- Conclusion and Future Work -- References -- Analyzing the Effect of Objective Correlation on  the Efficient Set of MNK-Landscapes -- Introduction -- Background -- Multiobjective Combinatorial Optimization -- Metaheuristics for Multiobjective Combinatorial Optimization -- NK- and MNK-Landscapes -- MNK-Landscapes: Multiobjective NK-Landscapes with Correlation -- Definition -- Correlation between Objective Functions."]
[{"$nulls":4},"Analysis of the Efficient Set Properties -- Cardinality of the Efficient Set -- Number of Supported Efficient Solutions -- Connectedness of the Efficient Set -- Discussion -- References -- Instance-Based Parameter Tuning via Search  Trajectory Similarity Clustering -- Introduction -- Preliminaries -- Automated Parameter Configuration Problem -- One-Size-Fits-All Configurator -- Instance-Based Configurator -- Performance Metric -- Solution Approach -- Search Trajectory Similarity -- Search Trajectory Representation -- Similarity Calculation -- Clustering Method -- Training and Testing Phases -- Experimental Design -- Experiment Settings -- Validity and Statistical Significant Measurement -- Experimental Setup -- Empirical Evaluation -- Performance Comparison -- Comparison on Feature Selection -- "]
[{"$nulls":4},"Sensitivity Analysis on Different Initial Sequence Configurations -- Computational Results -- Discussion -- Conclusion and Future Works -- References -- Effective Probabilistic Stopping Rules for  Randomized Metaheuristics: GRASP Implementations -- Introduction and Motivation -- GRASP and Experimental Environment -- Normal Approximation for GRASP Iterations -- Probabilistic Stopping Rule -- Concluding Remarks -- References -- A Classifier-Assisted Framework for Expensive  Optimization Problems: A Knowledge-Mining Approach -- Introduction -- Background -- Expensive Optimization Problems -- Simulator Infeasible Vectors -- Proposed Framework -- The Model -- The Classifier -- The Framework -- Performance Analysis -- Test Problem and Benchmarks -- Knowledge-Mining the Classifier -- Summary -- References -- Robust Gaussian Process-Based  Global Optimization Using a Fully Bayesian Expected Improvement Criterion -- Introduction -- Efficient Global Optimization -- The Expected Improvement Sampling Criterion for a Gaussian Process."]
[{"$nulls":4},"Classical Parametrized Covariance Functions -- The EGO Algorithm -- The Case of Deceptive Functions -- Fully Bayesian One-Step Lookahead Optimization -- Student EI -- Numerical Experiments -- Optimization of a Deceptive Function -- Comparison on Sample Paths of a Gaussian Process -- References -- Hierarchical Hidden Conditional Random Fields  for Information Extraction -- Introduction -- Hierarchical Hidden Conditional Random Fields -- Information Extraction -- Paper Organization -- HHMMs -- Representing an HHMM as a DBN -- HHCRFs -- Model -- Parameter Estimation -- Sentence Representation -- Hierarchical Models for Information Extraction -- Upper and Lower Levels -- Model Learning -- Inference -- Experiments -- Data -- Retrieved Results -- Performance Evaluation -- Results -- Conclusion -- References -- Solving Extremely Difficult MINLP Problems Using  Adaptive Resolution Micro-GA with Tabu Search -- Introduction -- Related Work -- GAs for Solving MINLP Problems -- The Proposed Algorithm -- Variables Encoding and Genetic Operators -- Constraint Handling -- Micro GA -- Adaptive Resolution Approach -- Local Search -- Avoiding Redundancy -- Results -- Environment and Parameters -- Results and Discussion -- Conclusions and Future Work -- References -- Adaptive Abnormality Detection on ECG Signal by  Utilizing FLAC Features -- Introduction -- Architecture of the Proposed Framework -- Preprocessing in Frequency Domain -- Local Auto-correlation on Complex Fourier Values (FLAC) for ECG -- Complex Subspace Method -- Experiments -- Conclusions -- References -- Gravitational Interactions Optimization -- Introduction -- Review GSA GIO and CSS -- Newton's Law of Universal Gravitation -- Gravitational Interactions Optimization -- Gravitational Interactions for Unimodal Optimization -- Gravitational Interactions for Multimodal Optimization -- Experiments."]
[{"$nulls":4},"Test Functions -- Results -- Conclusions -- References -- On the Neutrality of Flowshop Scheduling Fitness Landscapes -- Motivations -- Background -- Definition of the Permutation Flowshop Scheduling Problem -- Neighborhood and Local Search -- Fitness Landscape -- Neutral Networks Analysis for the Permutation Flowshop Scheduling Problem -- Experimental Design -- Neutral Degree -- Typology of Neutral Networks -- Exploiting Neutrality to Solve the FSP -- Reaching Portals -- How to Guide the Search? -- Discussion -- References -- A Reinforcement Learning Approach for the  Flexible Job Shop Scheduling Problem -- Introduction -- Flexible Job Shop Scheduling Problem -- Problem Formulation -- Previous Approaches -- Dispatching Rules -- Reinforcement Learning -- Q-Learning -- The Proposed Approach: Learning / Optimization -- Pseudo-code of the Algorithm -- Example "]
[{"$nulls":4},"-- Experimental Results -- Instances -- Parameters -- Comparative Study -- Conclusions and Future Work -- References -- Supervised Learning Linear Priority Dispatch  Rules for Job-Shop Scheduling -- Introduction -- Priority Dispatch Rules for Job-Shop Scheduling -- Logistic Regression -- Experimental Study -- Data Generation -- Training Size and Accuracy -- Comparison with Single Priority Dispatching Rules -- Robustness towards Data Distributions -- Fixed Weights -- Summary and Conclusion -- References -- Fine-Tuning Algorithm Parameters Using the Design of  Experiments Approach -- Introduction -- Automated Tuning Framework -- Screening Phase -- Exploration Phase -- Exploitation Phase -- Experimental Results -- Traveling Salesman Problem (TSP) -- Quadratic Assignment Problem (QAP) -- Conclusion -- References -- MetaHybrid: Combining Metamodels and  Gradient-Based Techniques in a Hybrid Multi-Objective Genetic Algorithm -- GA Elements: Focus on Elitism -- SQP Elements: Focus on Constraints."]
[{"$nulls":4},"Metamodels Derivatives."]
[null,null,null,"Sommario/riassunto","This book constitutes the thoroughly refereed post-conference proceedings of the 5th International Conference on Learning and Intelligent Optimization, LION 5, held in Rome, Italy, in January 2011. The 32 revised regular and 3 revised short papers were carefully reviewed and selected from a total of 99 submissions. In addition to the contributions to the general track there are 11 full papers and 3 short papers presented at the following four special sessions; IMON: Intelligent Multiobjective OptimizatioN, LION-PP: Performance Prediction Self* EAs: Self-tuning, self-configuring and self-generating evolutionary algorithms LION-SWAP: Software and Applications."]
[null,"2.","Record Nr.",null,"UNISA996214130203316"]
[null,null,"Titolo",null,"Mineralogia Polonica"]
[null,null,"Pubbl/distr/stampa",null,"Warszawa, : Wydawn. Geologiczne"]
[null,null,"Descrizione fisica",null,"1 online resource"]
[null,null,"Disciplina",null,"549.9/438"]
[null,null,"Soggetti",null,"Mineralogy - Poland"]
[{"$nulls":4},"Mineralogy"]
[{"$nulls":4},"Periodicals."]
[{"$nulls":4},"Poland"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Periodico"]
[null,null,null,"Note generali","Refereed/Peer-reviewed"]
[null,"3.","Record Nr.",null,"UNICAMPANIAVAN00118079"]
[null,null,"Titolo",null,"Atti 2011-2012 / Accademia Nazionale di San Luca ; [direttore responsabile Francesco Moschini]"]
[null,null,"Pubbl/distr/stampa",null,"Roma, : Accademia Nazionale di San Luca, 2013"]
[null,null,"ISBN",null,"978-88-976101-1-3"]
[null,null,"Descrizione fisica",null,"488 p. : ill. ; 30 cm."]
[null,null,"Soggetti",null,"*Accademia nazionale di San Luca - Attività - 2011-2012"]
[null,null,"Lingua di pubblicazione",null,"Italiano"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]