Learning and Intelligent Optimization : 10th International Conference, LION 10, Ischia, Italy, May 29 -- June 1, 2016, Revised Selected Papers / edited by Paola Festa, Meinolf Sellmann, Joaquin Vanschoren.

Format:

Book

Contributor:

Festa, Paola, editor.

Sellmann, Meinolf, editor.

Vanschoren, Joaquin, editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

LNCS sublibrary. Theoretical computer science and general issues ; SL 1, 10079.

Theoretical Computer Science and General Issues ; 10079

Language:

English

Subjects (All):

Algorithms.

Computer logic.

Artificial intelligence.

Computer science--Mathematics.

Computer science.

Computers.

Computer simulation.

Algorithm Analysis and Problem Complexity.

Logics and Meanings of Programs.

Artificial Intelligence.

Discrete Mathematics in Computer Science.

Computation by Abstract Devices.

Simulation and Modeling.

Local Subjects:

Algorithm Analysis and Problem Complexity.

Logics and Meanings of Programs.

Artificial Intelligence.

Discrete Mathematics in Computer Science.

Computation by Abstract Devices.

Simulation and Modeling.

Physical Description:

1 online resource (XI, 309 pages) : 74 illustrations.

Edition:

First edition 2016.

Contained In:

Springer eBooks

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2016.

System Details:

text file PDF

Summary:

This book constitutes the thoroughly refereed post-conference proceedings of the 10th International Conference on Learning and Optimization, LION 10, which was held on Ischia, Italy, in May/June 2016. The 14 full papers presented together with 9 short papers and 2 GENOPT papers were carefully reviewed and selected from 47 submissions. The papers address all fields between machine learning, artificial intelligence, mathematical programming and algorithms for hard optimization problems. Special focus is given to new ideas and methods; challenges and opportunities in various application areas; general trends, and specific developments.

Contents:

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.

Other Format:

Printed edition:

ISBN:

978-3-319-50349-3

9783319503493

Access Restriction:

Restricted for use by site license.