LEADER 00397nam 2200157z- 450 001 996320166603316 035 $a(CKB)4210000000000548 035 $a(EXLCZ)994210000000000548 100 $a20160606c1901uuuu -u- - 101 0 $aeng 200 10$aEgyptian magic 701 $aBudge$b E. A. Wallis$0747676 906 $aBOOK 912 $a996320166603316 996 $aEgyptian magic$92340541 997 $aUNISA LEADER 12855nam 22008175 450 001 996465339903316 005 20230329144429.0 010 $a3-319-69404-9 024 7 $a10.1007/978-3-319-69404-7 035 $a(CKB)4100000000881982 035 $a(DE-He213)978-3-319-69404-7 035 $a(MiAaPQ)EBC6287739 035 $a(MiAaPQ)EBC5591645 035 $a(Au-PeEL)EBL5591645 035 $a(OCoLC)1009042334 035 $a(PPN)220121575 035 $a(EXLCZ)994100000000881982 100 $a20171025d2017 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aLearning and Intelligent Optimization$b[electronic resource] $e11th International Conference, LION 11, Nizhny Novgorod, Russia, June 19-21, 2017, Revised Selected Papers /$fedited by Roberto Battiti, Dmitri E. Kvasov, Yaroslav D. Sergeyev 205 $a1st ed. 2017. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2017. 215 $a1 online resource (XIII, 390 p. 92 illus.) 225 1 $aTheoretical Computer Science and General Issues,$x2512-2029 ;$v10556 311 $a3-319-69403-0 320 $aIncludes bibliographical references and index. 327 $aIntro -- Preface -- Organization -- Contents -- Long Papers -- An Importance Sampling Approach to the Estimation of Algorithm Performance in Automated Algorithm Design -- 1 Introduction -- 2 The Algorithm Design Problem (ADP) -- 3 Performance Estimation in PbO -- 3.1 Prior Art -- 3.2 An Importance Sampling Approach -- 4 Envisioned Benefits -- 5 Theoretical Feasibility -- 6 The Proof of Concept -- 6.1 Practical Challenges -- 6.2 High-Level Search Strategy -- 7 Experiments -- 7.1 Experimental Setup -- 7.2 Results and Discussion -- 8 Conclusion -- References -- Test Problems for Parallel Algorithms of Constrained Global Optimization -- 1 Introduction -- 2 Problem Statement -- 3 Generating a Series of Problems -- 4 Parallel Global Optimization Index Algorithm -- 5 Results of Numerical Experiments -- 6 Conclusion -- References -- Automatic Configuration of Kernel-Based Clustering: An Optimization Approach -- Abstract -- 1 Introduction -- 2 Material and Methods -- 2.1 Notation -- 2.2 The Case Study and the Data Generation Process -- 2.3 Kernel K-means -- 3 Hyperparameter Optimization of the Unsupervised Learning Phase of the Machine Learning Pipeline -- 3.1 Hyperparameters in the Pipeline: The Design Variables -- 3.2 Clustering Performance: The Objective Function -- 3.3 Sequential Model Based Optimization -- 3.3.1 Building the Surrogate of the Objective Function: Gaussian Processes and Random Forest -- 3.3.2 Acquisition Function: Confidence Bound -- 3.3.3 Termination Criterion -- 3.3.4 Software Environment -- 4 Results and Discussion -- 5 Conclusions -- References -- Solution of the Convergecast Scheduling Problem on a Square Unit Grid When the Transmission Range is 2 -- 1 Introduction -- 2 General Problem Formulation -- 3 CSP in the Unit Square Grid When the Transmission Distance is 2 -- 3.1 The Exact Lower Bound for the Schedule Length. 327 $a3.2 Algorithm A -- 4 Conclusion -- References -- A GRASP for the Minimum Cost SAT Problem -- 1 Introduction -- 2 Mathematical Formulation of the Problem -- 3 A GRASP for MinCostSAT -- 4 Probabilistic Stopping Rule -- 4.1 Fitting Data Procedure -- 4.2 Improve Probability Procedure -- 5 Results -- 6 Conclusions -- References -- A New Local Search for the p-Center Problem Based on the Critical Vertex Concept -- 1 Introduction -- 2 GRASP Construction Phase -- 3 Plateau Surfer: A New Local Search Based on the Critical Vertex Concept -- 4 Experimental Results -- 5 Concluding Remarks -- References -- An Iterated Local Search Framework with Adaptive Operator Selection for Nurse Rostering -- 1 Introduction -- 2 The Nurse Rostering Problem -- 3 The Proposed Approach -- 3.1 Credit Assignment Module -- 3.2 Action Selection Methodology -- 4 Experimental Results -- 4.1 Experimental Setup -- 4.2 Experimental Results and Analysis -- 5 Conclusions -- References -- Learning a Reactive Restart Strategy to Improve Stochastic Search -- 1 Introduction -- 2 Restart Strategies -- 3 Learning Dynamic Parameter Updates -- 4 A Hyper-Parameterized Restart Strategy -- 4.1 Features -- 4.2 Turning Features into Scores -- 4.3 The Reactive Restart Framework -- 5 Experimental Analysis -- 5.1 Problems and Benchmarks -- 5.2 Data Collection -- 5.3 Training of Hyper -- 5.4 Results -- 6 Conclusion -- References -- Efficient Adaptive Implementation of the Serial Schedule Generation Scheme Using Preprocessing and Bloom Filters -- 1 Introduction -- 2 SSGS Implementation Details -- 2.1 Initialisation of A -- 2.2 Efficient Search of the Earliest Feasible Slot for a Job -- 2.3 Preprocessing and Automated Parameter Control -- 3 SSGS Implementation Using Bloom Filters -- 3.1 Optimisation of Bloom Filter Structure -- 3.2 Additional Speed-ups -- 4 Hybrid Control Mechanism -- 5 Empirical Evaluation. 327 $a6 Conclusions and Future Work -- References -- Interior Point and Newton Methods in Solving High Dimensional Flow Distribution Problems for Pipe Networks -- 1 Introduction -- 2 Problem Statement -- 3 Newton Method -- 4 Interior Point Method -- 5 Matrices Multiplication in Interior Point Method -- 6 Acceleration by Constant Multiplication -- 7 Combined Method for Constrained Problem -- 8 Numerical Results -- 9 Conclusion -- References -- Hierarchical Clustering and Multilevel Refinement for the Bike-Sharing Station Planning Problem -- 1 Introduction -- 2 Related Work -- 3 Problem Formalization -- 3.1 Solution Representation -- 3.2 Objective -- 3.3 Calculation of Fulfilled Customer Demand -- 3.4 Calculation of Rebalancing Costs -- 4 Multilevel Refinement Approach -- 4.1 Coarsening -- 4.2 Initialization -- 4.3 Extension -- 5 Computational Results -- 6 Conclusion and Future Work -- References -- Decomposition Descent Method for Limit Optimization Problems -- 1 Introduction -- 2 Auxiliary Problem Properties -- 3 Limit Decomposition Method and its Convergence -- 4 Modifications and Applications -- 5 Computational Experiments -- 6 Conclusions -- References -- RAMBO: Resource-Aware Model-Based Optimization with Scheduling for Heterogeneous Runtimes and a Comparison with Asynchronous Model-Based Optimization -- 1 Introduction -- 2 Model-Based Global Optimization -- 2.1 Parallel MBO -- 3 Resource-Aware Scheduling with Synchronous Model Update -- 3.1 Infill Criterion - Priority -- 3.2 Resource Estimation -- 3.3 Resource-Aware Knapsack Scheduling -- 3.4 Refinement of Job Priorities via Clustering -- 4 Numerical Experiments -- 4.1 Quality of Resource Estimation -- 4.2 High Runtime Estimation Quality: rosenbrock -- 4.3 Low Runtime Estimation Quality: rastrigin -- 5 Conclusion -- References -- A New Constructive Heuristic for the No-Wait Flowshop Scheduling Problem. 327 $a1 Introduction -- 2 The No-Wait Flowshop Scheduling Problem -- 2.1 Description of the Problem -- 2.2 State-of-the-Art -- 3 IBI: Iterated Best Insertion Heuristic -- 3.1 Analysis of Optimal Solutions Structure -- 3.2 Design of IBI -- 3.3 Experimental Analysis of Parameters -- 4 Experiments -- 4.1 Efficiency of IBI -- 4.2 IBI as Initialization of a Local Search -- 5 Conclusion and Perspectives -- References -- Sharp Penalty Mappings for Variational Inequality Problems -- 1 Introduction -- 2 Notations and Preliminaries -- 3 Sharp Penalty Mappings -- 4 Iteration Algorithm -- 5 Conclusions -- References -- A Nonconvex Optimization Approach to Quadratic Bilevel Problems -- 1 Introduction -- 2 Statement of the Problem and Its Reduction -- 3 The Local Search -- 4 Global Optimality Conditions and the Global Search Procedure -- 5 Computational Simulation -- 6 Conclusion -- References -- An Experimental Study of Adaptive Capping in irace -- 1 Introduction -- 2 Elitist Iterated Racing in irace -- 3 ParamILS and Adaptive Capping -- 4 Adaptive Capping in irace -- 5 Experiments -- 5.1 Experimental Setup -- 5.2 Experimental Results -- 5.3 Additional Analysis of iracecap -- 6 Comparison to Other Configurators -- 7 Conclusions -- References -- Duality Gap Analysis of Weak Relaxed Greedy Algorithms -- 1 Introduction -- 2 Weak Relaxed Greedy Algorithms -- 3 Dual Convergence Results -- 3.1 Duality Gap -- 3.2 Dual Convergence Result for WRGA(co) -- 3.3 Dual Convergence Result for WRGA() -- 4 Conclusion -- References -- Controlling Some Statistical Properties of Business Rules Programs -- 1 Introduction -- 1.1 Preliminaries -- 1.2 Related Works -- 2 Learning Goals with Histograms -- 2.1 A MIP for Learning Quantized Distributions -- 2.2 A MILP for the Max Percentage Problem -- 2.3 A MILP for the Almost Uniform Distribution Problem -- 3 Implementation and Experiments. 327 $a3.1 The Max Percentage Problem -- 3.2 The Almost Uniform Distribution Problem -- 4 Conclusion, Discussion and Future Work -- References -- GENOPT Paper -- Hybridization and Discretization Techniques to Speed Up Genetic Algorithm and Solve GENOPT Problems -- Abstract -- 1 Introduction -- 2 Preliminary Concepts -- 3 The GABRLS Algorithm -- 3.1 The Modified GA -- 3.2 Bounding Restart (BR) Technique -- 3.3 Hybridizing GABR with Local Searches -- 4 Tuning and Results of GABRLS on GENOPT Challenge -- 4.1 High Level Setting -- 4.2 Results and Prizes -- 5 Conclusion -- References -- Short Papers -- Identification of Discontinuous Thermal Conductivity Coefficient Using Fast Automatic Differentiation -- Abstract -- 1 Introduction -- 2 Formulation of the Problem -- 3 Numerical Solution of the Problem -- Acknowledgments -- References -- Comparing Two Approaches for Solving Constrained Global Optimization Problems -- 1 Introduction -- 2 Index Method -- 3 Results of Experiments -- 4 Conclusion -- References -- Towards a Universal Modeller of Chaotic Systems -- 1 Introduction -- 2 Previous Work -- 3 Learning Algorithm -- 3.1 Idle Mode -- 4 Experimental Setup -- 4.1 Repetition -- 4.2 Fractal Dimension -- 4.3 Lyapunov Exponent -- 5 Results -- 6 Conclusion -- References -- An Approach for Generating Test Problems of Constrained Global Optimization -- 1 Introduction -- 2 Test Problem Classes -- 3 Some Numerical Results -- 4 Conclusion -- References -- Global Optimization Using Numerical Approximations of Derivatives -- 1 Introduction -- 2 One-Dimensional Global Optimization Algorithm Using Numerical Estimations of Derivatives -- 2.1 Core One-Dimensional Global Search Algorithm Using Derivatives -- 2.2 One-Dimensional Global Search Algorithm Using Numerical Derivatives -- 3 Results of Computational Experiments -- 4 Conclusion -- References. 327 $aGlobal Optimization Challenges in Structured Low Rank Approximation. 330 $aThis book constitutes the thoroughly refereed post-conference proceedings of the 11th International Conference on Learning and Intelligent Optimization, LION 11, held in Nizhny,Novgorod, Russia, in June 2017. The 20 full papers (among these one GENOPT paper) and 15 short papers presented have been carefully reviewed and selected from 73 submissions. The papers explore the advanced research developments in such interconnected fields as mathematical programming, global optimization, machine learning, and artificial intelligence. Special focus is given to advanced ideas, technologies, methods, and applications in optimization and machine learning. 410 0$aTheoretical Computer Science and General Issues,$x2512-2029 ;$v10556 606 $aAlgorithms 606 $aComputer science 606 $aArtificial intelligence 606 $aNumerical analysis 606 $aComputer simulation 606 $aAlgorithms 606 $aComputer Science Logic and Foundations of Programming 606 $aArtificial Intelligence 606 $aNumerical Analysis 606 $aTheory of Computation 606 $aComputer Modelling 615 0$aAlgorithms. 615 0$aComputer science. 615 0$aArtificial intelligence. 615 0$aNumerical analysis. 615 0$aComputer simulation. 615 14$aAlgorithms. 615 24$aComputer Science Logic and Foundations of Programming. 615 24$aArtificial Intelligence. 615 24$aNumerical Analysis. 615 24$aTheory of Computation. 615 24$aComputer Modelling. 676 $a006.31 702 $aBattiti$b Roberto$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aKvasov$b Dmitri E$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aSergeyev$b Yaroslav D$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996465339903316 996 $aLearning and Intelligent Optimization$9773725 997 $aUNISA LEADER 00870nam a2200229 i 4500 001 991001797609707536 005 20020507151835.0 008 000210s1997 sp ||| | ita 020 $a9683658903 035 $ab11565482-39ule_inst 035 $aLE02725367$9ExL 040 $aDip.to Studi Giuridici$bita 084 $aC-XVIII/A 100 1 $aDe Cabo Cartin, Carlos$0528620 245 10$aContra el consenso :$bestudios sobre el estado constitucionalismo del estado social /$cCarlos De Cabo Cartin 260 $aMexico :$bUniv. 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