Artificial evolution [electronic resource] : 14th International Conference, Évolution Artificielle, EA 2019, Mulhouse, France, October 29-30, 2019, Revised selected papers

Responsibility
Lhassane Idoumghar, Pierrick Legrand, Arnaud Liefooghe, Evelyne Lutton, Nicolas Monmarché, Marc Schoenauer (eds.).
Digital
text file
PDF
Imprint
Cham : Springer, 2020.
Physical description
1 online resource
Series
Lecture notes in computer science ; 12052.
LNCS sublibrary. SL 1, Theoretical computer science and general issues.

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Contents/Summary

Bibliography
References-Fast Evolutionary Algorithm for Solving Large-Scale Multi-objective Problems-1 Introduction-2 Proposed Approach-2.1 Archive-Based Algorithm-2.2 UAM with Selection of Next Parent Population-2.3 New Adaptive Crossover Operator-2.4 Modified Self-adaptive Gaussian Mutation-3 Experiments and Validation-3.1 Experimental Setup-3.2 Experimental Results-4 Conclusion-References-Looking for Energy Efficient Genetic Algorithms-1 Introduction-2 Considering Power Consumption in GAs-2.1 Population Size and Power Consumption
Contents
  • From Feature Selection to Continuous Optimization.- Evolving a Weighted Combination of Text Similarities for Authorship Attribution.- Image Signal Processor Parameter Tuning with Surrogate-assisted Particle Swarm Optimization.- Combinatorial Surrogate-assisted Optimization for Bus Stops Spacing Problem.- Optimization of a Checkers Player Using Neural and Metaheuristic Approaches.- A Novel Outlook on Feature Selection as a Multi-Objective Problem.- Fast Evolutionary Algorithm for Solving Large-scale Multi-objective Problems.- Looking for Energy Efficient Genetic Algorithms.- Evolving Fitness Landscapes with Complementary Fitness Functions.- Bayesian Immigrant Diploid Genetic Algorithm for Dynamic Environments.- Ant Colony Optimization Algorithm for a Transportation Problem in Home Health Care with the Consideration of Carbon Emissions.- Selective Vehicle Routing Problem: A Hybrid Genetic Algorithm Approach.- Fixed Jobs Multi-agent Scheduling Problem with Renewable Resources.- A Study of Recombination Operators for the Cyclic Bandwidth Problem.- Automatic Calibration of a Farm Irrigation Model: a Multi-modal Optimization Approach.- A Hybrid Evolutionary Algorithm for Offl ine UAV Path Planning.
  • (source: Nielsen Book Data)
Publisher's summary
This book constitutes the thoroughly refereed post-conference proceedings of the 14th International Conference on Artificial Evolution, EA 2019, held in Mulhouse, France, in October 2019. The 16 revised papers were carefully reviewed and selected from 33 submissions. The papers cover a wide range of topics in the field of artificial evolution, such as evolutionary computation, evolutionary optimization, co-evolution, artificial life, population dynamics, theory, algorithmic and modeling, implementations, application of evolutionary paradigms to the real world (industry, biosciences...), other biologically-inspired paradigms (swarm, artificial ants, artificial immune systems, cultural algorithms...), memetic algorithms, multi-objective optimization, constraint handling, parallel algorithms, dynamic optimization, machine learning and hybridization with other soft computing techniques.
(source: Nielsen Book Data)

Bibliographic information

Publication date
2020
Title variation
EA 2019
Series
Lecture Notes in Computer Science ; 12052
LNCS Sublibrary, SL 1, Theoretical Computer Science and General Issues
Note
Includes author index.
ISBN
9783030457150 (electronic bk.)
303045715X (electronic bk.)
9783030457167 (print)
3030457168
3030457141
9783030457143
DOI
10.1007/978-3-030-45715-0
Librarian view | Catkey: 13598033