Metaheuristics and Nature Inspired Computing (eBook, PDF)

9th International Conference, META 2023, Marrakech, Morocco, November 1-4, 2023, Revised Selected Papers
Redaktion: Dorronsoro, Bernabé; Talbi, El-Ghazali; Ellaia, Rachid

• Format: PDF

Produktbeschreibung

This book constitutes the refereed proceedings of the 9th International Conference on Metaheuristics and Nature Inspired Computing, META 2023, held in Marrakech, Morocco, during November 1-4, 2023.

The 19 full papers presented in this volume were carefully reviewed and selected from 42 submissions. The papers are divided into the following topical sections: combinatorial optimization; scheduling; continuous optimization; automatic metaheuristics tuning; optimization and machine learning; and applications.

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Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 280
• Erscheinungstermin: 14. September 2024
• Englisch
• ISBN-13: 9783031692574
• Artikelnr.: 72242170

Inhaltsangabe

Combinatorial Optimization: Mixed Integer Linear Programming Based Large Neighborhood Search Approaches for the Directed Feedback Vertex Set Problem.- Uniformly Deployed Sets in Computer Science and Optimisation.- A Simulated Annealing Based Approach for the Roman Domination Problem.- Metaheuristic Algorithms for Circle Packing Problem: A Comprehensive Review.- Ergodic Annealing: intelligent optimization under uncertainty.- Scheduling: High Performance Algorithms for the Unrelated Parallel Machines Scheduling Problem with a Common Server and Job-Sequence Dependent Setup Times.- A Honey Bee Mating Optimization HyperHeuristic for Patient Admission Scheduling Problem.- Network ow models for days o scheduling.- Continuous Optimization: Opposition Based Local Escaping Marine Predators Algorithm for Continuous Optimization; Impact of Structural Bias on the Sine Cosine Algorithm: A Theoretical Investigation Using the Signature Test; Success Rate Based Scaling Factor Adaptation in Dual-Population Di erential Evolution.- Automatic Metahuristics Tuning: A Study About Meta-Optimizing the NSGA-II Multi-Objective Evolutionary Algorithm.- Artificial Intelligence for Metaheuristic Parameter Setting.- Hyperheuristic as Tuning Tool of Generalized Swap Strategy.- Optimization & Machine Learning: An optimised version of di erential evolution heuristic for feature selection.- Machine Learning-based Per-Instance Algorithm Selection for High-Performance Subgraph Isomorphism Enumeration.- Applications: Memetic Algorithms for the Technician Routing and Scheduling Problem: Real Case Study of Energy Distribution System Operator (DSO).- Cluster images with AntClust: a clustering algorithm based on the chemical recognition system of ants.- EVADyR: a new dynamic resampling algorithm for optimizing noisy expensive systems.