Overview

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.

Full Product Details

Author:   Bernabé Dorronsoro ,  Rachid Ellaia ,  El-Ghazali Talbi
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   2024 ed.
Volume:   2016
ISBN:  

9783031692567

ISBN 10:   303169256
Pages:   280
Publication Date:   15 September 2024
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand  
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Table of Contents

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 flow models for days off 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 Differential 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 differential 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.

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