Learning and Intelligent Optimization : 12th International Conference, LION 12, Kalamata, Greece, June 10-15, 2018, Revised Selected Papers / edited by Roberto Battiti, Mauro Brunato, Ilias Kotsireas, Panos M. Pardalos.

Format:

Book

Contributor:

Battiti, Roberto, 1961- editor.

Brunato, Mauro, editor.

Kotsireas, Ilias, editor.

Pardalos, P. M. (Panos M.), 1954- editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

LNCS sublibrary. Theoretical computer science and general issues ; SL 1, 11353.

Theoretical Computer Science and General Issues ; 11353

Language:

English

Subjects (All):

Algorithms.

Artificial intelligence.

Computer science--Mathematics.

Computer science.

Numerical analysis.

Computer arithmetic and logic units.

Data structures (Computer science).

Algorithm Analysis and Problem Complexity.

Artificial Intelligence.

Discrete Mathematics in Computer Science.

Numeric Computing.

Arithmetic and Logic Structures.

Data Structures.

Local Subjects:

Algorithm Analysis and Problem Complexity.

Artificial Intelligence.

Discrete Mathematics in Computer Science.

Numeric Computing.

Arithmetic and Logic Structures.

Data Structures.

Physical Description:

1 online resource (XII, 474 pages) : 145 illustrations, 93 illustrations in color.

Edition:

First edition 2019.

Contained In:

Springer eBooks

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2019.

System Details:

text file PDF

Summary:

This book constitutes the thoroughly refereed post-conference proceedings of the 12th International Conference on Learning and Intelligent Optimization, LION 12, held in Kalamata, Greece, in June 2018. The 28 full papers and 12 short papers presented have been carefully reviewed and selected from 62 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.

Contents:

Accelerated Randomized Coordinate Descent Algorithms for Stochastic Optimization and Online Learning

An Improved BTK Algorithm Based on Cell-like P System with Active Membranes

A Simple Algorithmic Proof of the Symmetric Lopsided Lovász Local Lemma

Creating a Multi-Iterative-Priority-Rule for the Job Shop Scheduling Problem with Focus on Tardy Jobs via Genetic Programming

A Global Optimization Algorithm for Non-Convex Mixed-Integer Problems

Massive 2-opt and 3-opt Moves with High Performance GPU Local Search to Large-scale Traveling Salesman Problem

Instance-Specific Selection of AOS Methods for Solving Combinatorial Optimization Problems via Neural Networks

CAVE: Configuration Assessment, Visualization and Evaluation

The Accuracy of One Polynomial Algorithm for the Convergecast Scheduling Problem on a Square Grid with Rectangular Obstacles

An Effective Heuristic for a Single-Machine Scheduling Problem with Family Setups and Resource Constraints

Learning the Quality of Dispatch Heuristics Generated by Automated Programming

Explaining Heuristic Performance Differences for Vehicle Routing Problems with Time Windows

Targeting Well-Balanced Solutions in Multi-Objective Bayesian Optimization under a Restricted Budget

How Grossone Can Be Helpful to Iteratively Compute Negative Curvature Directions

Solving Scalarized Subproblems Within Evolutionary Algorithms for Multi-Criteria Shortest Path Problems

Exact and Heuristic Approaches for the Longest Common Palindromic Subsequence Problem

Multi-Objective Performance Measurement: Alternatives to PAR10 and Expected Running Time

Algorithm Configuration: Learning Policies for the Quick Termination of Poor Performers

Probability Estimation by An Adapted Genetic Algorithm in Web Insurance

Adaptive Multi-Objective Local Search Algorithms for the Permutation Flowshop Scheduling Problem

Portfolio Optimization Via a Surrogate Risk Measure: Conditional Desirability Value at Risk (CDVaR)

Rover Descent: Learning to Optimize by Learning to Navigate on Prototypical Loss Surfaces

Analysis of Algorithm Components and Parameters: Some Case Studies

Optimality of Multiple Decision Statistical Procedure for Gaussian Graphical : Model Selection

Hyper-Reactive Tabu Search for MaxSAT

Exact Algorithms for Two Quadratic Euclidean Problems of Searching for the Largest Subset and Longest Subsequence

A Restarting Rule Based on the Schnabel Census for Genetic Algorithms.-Intelligent Pump Scheduling Optimization in Water Distribution Networks Detecting Patterns in Benchmark Instances of the Swap-body Vehicle Routing Problem

Evolutionary Deep Learning for Car Park Occupancy Prediction in Smart Cities

Asymptotically Optimal Algorithm for the Maximum m-Peripatetic Salesman Problem in a Normed Space

Computational Intelligence for Locating Garbage Accumulation Points in Urban Scenarios

Fully Convolutional Neural Networks for Mapping Oil Palm Plantations in Kalimantan

Calibration of a Water Distribution Network with Limited Field Measures: the Case Study of Castellammare di Stabia (Naples, Italy)

Combinatorial Methods for Testing Communication Protocols in Smart Cities

Pseudo-pyramidal Tours and Efficient Solvability of the Euclidean Generalized Traveling Salesman Problem in Grid Clusters

Constant Factor Approximation for Intersecting Line Segments with Disks

Scheduling Deteriorating Jobs and Module Changes with Incompatible Job Families on Parallel Machines Using a Hybrid SADE-AFSA Algorithm.

Other Format:

Printed edition:

ISBN:

978-3-030-05348-2

9783030053482

Access Restriction:

Restricted for use by site license.