Estimation of Distribution Algorithms

Опубликована: Янв. 1, 2025

Язык: Английский

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Into the Black Box: Mining Variable Importance with XAI

Lecture notes in computer science, Год журнала: 2025, Номер unknown, С. 20 - 35

Опубликована: Янв. 1, 2025

Язык: Английский

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A systematic review of explainability in computational intelligence for optimization

Computer Science Review, Год журнала: 2025, Номер 57, С. 100764 - 100764

Опубликована: Май 22, 2025

Язык: Английский

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A Review of Benchmark and Test Functions for Global Optimization Algorithms and Metaheuristics

Wiley Interdisciplinary Reviews Computational Statistics, Год журнала: 2025, Номер 17(2)

Опубликована: Май 26, 2025

ABSTRACT Benchmarking in optimization is a critical step evaluating the performance, robustness, and scalability of machine learning algorithms metaheuristics. While trends benchmark design continue to evolve, synthetic functions remain vital for fundamental stress tests theoretical evaluations. As several test have been developed derived over past decades, little attention has given classifying such rationale behind their usage. From this lens, paper reviews categorizes broad range often employed assessing optimizers More specifically, we classify based on modality, dimensionality, separability, smoothness, constraints, noise characteristics offer view that aids selecting appropriate benchmarks various algorithmic challenges. Then, review also discusses detail 25 most commonly used open literature proposes two new, highly dimensional, dynamic, challenging could be testing new algorithms. Finally, identifies gaps current benchmarking practices directions future research, as well suggests best guidelines.

Язык: Английский

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Explaining a Staff Rostering Problem Using Partial Solutions

Lecture notes in computer science, Год журнала: 2024, Номер unknown, С. 179 - 193

Опубликована: Ноя. 28, 2024

Язык: Английский

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