A Metaheuristic Search Algorithm Based on Sampling and Clustering

A Metaheuristic Search Algorithm Based on Sampling and Clustering

As optimization problems become more complicated and extensive, parameterization becomes complex, resulting in a difficult task requiring significant amounts of time and resources. In this paper we propose a heuristic search algorithm we call MCSA (Montecarlo-Clustering Search Algorithm), which is b...

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Bibliographic Details
Main Authors: Maria Harita, Alvaro Wong, Remo Suppi, Dolores Rexachs, Emilio Luque
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Benchmarks
heuristic methods
Knapsack problem
Montecarlo and clustering methods
optimization
Online Access:https://ieeexplore.ieee.org/document/10403809/

Internet

https://ieeexplore.ieee.org/document/10403809/

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