Bounding the Multi-Scale Domain in Numerical Modelling and Meta-Heuristics Optimization: Application to Poroelastic Media with Damageable Cracks. [PDF]
Materials (Basel), 2021 Argilaga A, Papachristos E.
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Advanced Meta-Heuristics, Convolutional Neural Networks, and Feature Selectors for Efficient COVID-19 X-Ray Chest Image Classification. [PDF]
IEEE Access, 2021 El-Kenawy EM +6 more
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Choice Function-Based Hyper-Heuristics for Causal Discovery under Linear Structural Equation Models
BiomimeticsCausal discovery is central to human cognition, and learning directed acyclic graphs (DAGs) is its foundation. Recently, many nature-inspired meta-heuristic optimization algorithms have been proposed to serve as the basis for DAG learning.
Yinglong Dang +2 more
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Boolean Operators to Improve Multi-Objective Evolutionary Algorithms for Designing Optical Networks
Journal of Microwaves, Optoelectronics and Electromagnetic ApplicationsThe physical topology design (PTD) of optical networks is frequently accomplished by combining several solutions in an iterative way, especially if meta-heuristics are deployed for this purpose.
Nadja J. da S. Lima +2 more
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Special issue on "real-world optimization problems and meta-heuristics". [PDF]
Neural Comput Appl, 2020 Mirjalili S.
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Fast Ejection Chain Algorithms for Vehicle Routing with Time Windows [PDF]
This paper introduces new ejection chain strategies to effectively target vehicle routing problems with time window constraints (VRPTW). Ejection chain procedures are based on the idea of compound moves that allow a variable number of solution components
Horn,S.P.,van der +3 more
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Feasibility restoration for iterative meta-heuristics search algorithms [PDF]
, 2002 Randall, Marcus
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BizInfoToday, the algorithm selection paradigm has become one of the promising approaches in the field of optimization problems. Its main goal is to solve each case of an optimization problem with the most accurate algorithm using machine learning techniques ...
Ahmed Adnane Abdessemed +3 more
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Global Optimization strategies for two-mode clustering [PDF]
Two-mode clustering is a relatively new form of clustering that clusters both rows and columns of a data matrix. To do so, a criterion similar to k-means is optimized.
Castilli, W. +3 more
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EFFICIENCY OF SELECTED META-HEURISTICS APPLIED TO THE TSP PROBLEM: A SIMULATION STUDY
TASK Quarterly, 2003 The paper presents a simulation study of the usefulness of a number of meta-heuristics used as optimisation methods for TSP problems. The five considered approaches are outlined: Genetic Algorithm, Simulated Annealing, Ant Colony System, Tabu Search and
HALINA KWAŚNICKA
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