Learning and Intelligent Optimization
-15%
portes grátis
Learning and Intelligent Optimization
10th International Conference, LION 10, Ischia, Italy, May 29 -- June 1, 2016, Revised Selected Papers
Festa, Paola; Sellmann, Meinolf; Vanschoren, Joaquin
Springer International Publishing AG
12/2016
309
Mole
Inglês
9783319503486
15 a 20 dias
498
Descrição não disponível.
Learning a stopping criteria for Local Search.- Surrogate Assisted Feature Computation for Continuous Problems.- MO-ParamILS: A Multi-objective Automatic Algorithm Configuration Framework.- Evolving Instances for Maximizing Performance Differences of State-of-The-Art Inexact TSP Solvers.- Extreme Reactive Portfolio (XRP): Tuning an Algorithm Population for Global Optimization.- Bounding the Search Space of the Population Harvest Cutting Problem with Multiple Size Stock Selection.- Designing and comparing multiple portfolios of parameter configurations for online algorithm selection.- Portfolios of Subgraph Isomorphism Algorithms.- Structure-preserving Instance Generation.- Feature Selection using Tabu Search with Learning Memory: Learning Tabu Search.- The Impact of Automated Algorithm Configuration on the Scaling Behaviour of State-of-the-art Inexact TSP Solvers.- Requests Management for Smartphone-based Matching Applications using a Multi-Agent Approach.- Self-Organizing Neural Network for Adaptive Operator Selection in Evolutionary Search.- Quantifying the Similarity of Algorithm Configurations.- Neighborhood synthesis from an ensemble of MIP and CP models.- Parallelizing Constraint Solvers for Hard RCPSP Instances.- Characterization of neighborhood behaviours in a multi-neighborhood local search algorithm.- Constraint Programming and Machine Learning for Interactive Soccer Analysis.- A Matheuristic Approach for the p-Cable Trench Problem.- An Empirical Study of Per-Instance Algorithm Scheduling.- Dynamic strategy to diversify search using history map in parallel solving.- Faster Model Based Optimization through Resource Aware Scheduling Strategies.- Risk-Averse Anticipation for Dynamic Vehicle Routing.- Solving GENOPT problems with the use of ExaMin solver.- Hybridisation of Evolutionary Algorithms through Hyper-heuristics for Global Continuous Optimisation.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
algorithm selection;discrete mathematics;machine learning;mathematical optimization;meta-learning;algorithm configuration;black-box optimization;clustering;combinatorial optimization;constraint solving;differential evolution;dynamic vehicle routing;empirical study;feature extraction;feature selection;genetic algorithm;machine learning theory;meta-heuristics;probability and statistics;algorithm analysis and problem complexity
Learning a stopping criteria for Local Search.- Surrogate Assisted Feature Computation for Continuous Problems.- MO-ParamILS: A Multi-objective Automatic Algorithm Configuration Framework.- Evolving Instances for Maximizing Performance Differences of State-of-The-Art Inexact TSP Solvers.- Extreme Reactive Portfolio (XRP): Tuning an Algorithm Population for Global Optimization.- Bounding the Search Space of the Population Harvest Cutting Problem with Multiple Size Stock Selection.- Designing and comparing multiple portfolios of parameter configurations for online algorithm selection.- Portfolios of Subgraph Isomorphism Algorithms.- Structure-preserving Instance Generation.- Feature Selection using Tabu Search with Learning Memory: Learning Tabu Search.- The Impact of Automated Algorithm Configuration on the Scaling Behaviour of State-of-the-art Inexact TSP Solvers.- Requests Management for Smartphone-based Matching Applications using a Multi-Agent Approach.- Self-Organizing Neural Network for Adaptive Operator Selection in Evolutionary Search.- Quantifying the Similarity of Algorithm Configurations.- Neighborhood synthesis from an ensemble of MIP and CP models.- Parallelizing Constraint Solvers for Hard RCPSP Instances.- Characterization of neighborhood behaviours in a multi-neighborhood local search algorithm.- Constraint Programming and Machine Learning for Interactive Soccer Analysis.- A Matheuristic Approach for the p-Cable Trench Problem.- An Empirical Study of Per-Instance Algorithm Scheduling.- Dynamic strategy to diversify search using history map in parallel solving.- Faster Model Based Optimization through Resource Aware Scheduling Strategies.- Risk-Averse Anticipation for Dynamic Vehicle Routing.- Solving GENOPT problems with the use of ExaMin solver.- Hybridisation of Evolutionary Algorithms through Hyper-heuristics for Global Continuous Optimisation.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
algorithm selection;discrete mathematics;machine learning;mathematical optimization;meta-learning;algorithm configuration;black-box optimization;clustering;combinatorial optimization;constraint solving;differential evolution;dynamic vehicle routing;empirical study;feature extraction;feature selection;genetic algorithm;machine learning theory;meta-heuristics;probability and statistics;algorithm analysis and problem complexity
