All Stories

  1. A survey of features used for representing black-box single-objective continuous optimization
  2. Behaviour Space Analysis of LLM-Driven Meta-Heuristic Discovery
  3. Mechanistic Interpretability for Transformer-Based Time Series Classification
  4. Agentic Large Language Models, a Survey
  5. Latest Approaches in Reasoning Large Language Models
  6. Quality–diversity-driven robust evolutionary optimization of optical designs
  7. LLaMEA: Automatically Generating Metaheuristics with Large Language Models
  8. BLADE: Benchmark suite for LLM-driven Automated Design and Evolution of iterative optimisation heuristics
  9. Explainable Benchmarking for Iterative Optimization Heuristics
  10. Neighborhood Adaptive Differential Evolution
  11. Structural bias in optimization algorithms
  12. Optimizing Photonic Structures with Large Language Model Driven Algorithm Discovery
  13. Code Evolution Graphs: Understanding Large Language Model Driven Design of Algorithms
  14. Explainable Benchmarking for Iterative Optimization Heuristics
  15. In-the-loop Hyper-Parameter Optimization for LLM-Based Automated Design of Heuristics
  16. LLaMEA: A Large Language Model Evolutionary Algorithm for Automatically Generating Metaheuristics
  17. Surrogate-based automated hyperparameter optimization for expensive automotive crashworthiness optimization
  18. Stalling in Space: Attractor Analysis for Any Algorithm
  19. Controlling the Mutation in Large Language Models for the Efficient Evolution of Algorithms
  20. XAI for Benchmarking Black-Box Metaheuristics
  21. Explainable AI for Evolutionary Computation
  22. An Introduction to the Crossroads of Explainable Artificial Intelligence and Evolutionary Computation
  23. ACO-NSGAII: A Novel Metaheuristics for Bi-Objective Electric Vehicle Routing Problems
  24. A Functional Analysis Approach to Symbolic Regression
  25. A Corridor Model Evolutionary Algorithm for Fast Converging Green Vehicle Routing Problem
  26. A Critical Analysis of Raven Roost Optimization
  27. Modular Optimization Framework for Mixed Expensive and Inexpensive Real-World Problems
  28. Hot off the Press: Parallel Multi-Objective Optimization for Expensive and Inexpensive Objectives and Constraints
  29. Landscape Analysis Based vs. Domain-Specific Optimization for Engineering Design Applications: A Clear Case
  30. Quality-diversity driven robust evolutionary optimization of optical designs
  31. Parallel multi-objective optimization for expensive and inexpensive objectives and constraints
  32. Generating Cheap Representative Functions for Expensive Automotive Crashworthiness Optimization
  33. A Deep Dive Into Effects of Structural Bias on CMA-ES Performance Along Affine Trajectories
  34. Evolutionary Computation and Explainable AI: A Roadmap to Understandable Intelligent Systems
  35. TX-Gen: Multi-Objective Optimization for Sparse Counterfactual Explanations for Time-Series Classification
  36. Towards Fairness in Machine Learning: Balancing Racially Imbalanced Datasets Through Data Augmentation and Generative AI
  37. Beyond the Veil of Similarity: Quantifying Semantic Continuity in Explainable AI
  38. Landscape-Aware Automated Algorithm Configuration Using Multi-output Mixed Regression and Classification
  39. Clustering-based Domain-Incremental Learning
  40. Curing ill-Conditionality via Representation-Agnostic Distance-Driven Perturbations
  41. New solutions to Cooke triplet problem via analysis of attraction basins
  42. DoE2Vec: Deep-learning Based Features for Exploratory Landscape Analysis
  43. Deep BIAS: Detecting Structural Bias using Explainable AI
  44. AI for Expensive Optimization Problems in Industry
  45. Application of Functional Kernel Hypothesis Testing for Channel Selection in Time Series Classification
  46. Evaluation of deep unsupervised anomaly detection methods with a data-centric approach for on-line inspection
  47. BBOB Instance Analysis: Landscape Properties and Algorithm Performance Across Problem Instances
  48. Challenges of ELA-Guided Function Evolution Using Genetic Programming
  49. A data-centric approach to anomaly detection in layer-based additive manufacturing
  50. Evolutionary Algorithms for Parameter Optimization—Thirty Years Later
  51. The Opaque Nature of Intelligence and the Pursuit of Explainable AI
  52. Multi-surrogate Assisted Efficient Global Optimization for Discrete Problems
  53. BIAS: A Toolbox for Benchmarking Structural Bias in the Continuous Domain
  54. GSAreport: Easy to Use Global Sensitivity Reporting
  55. A Comparison of Global Sensitivity Analysis Methods for Explainable AI with an Application in Genomic Prediction
  56. A Comparison of Global Sensitivity Analysis Methods for Explainable AI with an Application in Genomic Prediction
  57. Analysis of how bias in search algorithms can affect the search behaviour
  58. Exploratory Landscape Analysis in Real-World Engineering Optimization
  59. Multi-point acquisition function for constraint parallel efficient multi-objective optimization
  60. End-to-End Pipeline for Uncertainty Quantification and Remaining Useful Life Estimation: An Application on Aircraft Engines
  61. Explainable Artificial Intelligence for Exhaust Gas Temperature of Turbofan Engines
  62. Constrained Multi-Objective Optimization with a Limited Budget of Function Evaluations
  63. Multitask Shape Optimization Using a 3-D Point Cloud Autoencoder as Unified Representation
  64. Optimally Weighted Ensembles for Efficient Multi-objective Optimization
  65. Analysis of Structural Bias in Differential Evolution Configurations
  66. A Comparison of many Global Sensitivity Analysis methods
  67. Exploiting Generative Models for Performance Predictions of 3D Car Designs
  68. Using Machine Learning to Detect Rotational Symmetries from Reflectional Symmetries in 2D Images
  69. Point2FFD: Learning Shape Representations of Simulation-Ready 3D Models for Engineering Design Optimization
  70. BIAS: A Toolbox for Benchmarking Structural Bias in the Continuous Domain
  71. BIAS: A Toolbox for Benchmarking Structural Bias in the Continuous Domain
  72. Emergence of structural bias in differential evolution
  73. Exploiting Local Geometric Features in Vehicle Design Optimization with 3D Point Cloud Autoencoders
  74. SAMO-COBRA: A Fast Surrogate Assisted Constrained Multi-objective Optimization Algorithm
  75. Requirements towards optimizing analytics in industrial processes
  76. A Tailored NSGA-III for Multi-objective Flexible Job Shop Scheduling
  77. Back To Meshes: Optimal Simulation-ready Mesh Prototypes For Autoencoder-based 3D Car Point Clouds
  78. Neural Network Design: Learning from Neural Architecture Search
  79. Improving NSGA-III for flexible job shop scheduling using automatic configuration, smart initialization and local search
  80. Feature Visualization for 3D Point Cloud Autoencoders
  81. A New Approach Towards the Combined Algorithm Selection and Hyper-parameter Optimization Problem
  82. On the Efficiency of a Point Cloud Autoencoder as a Geometric Representation for Shape Optimization
  83. Scalability of Learning Tasks on 3D CAE Models Using Point Cloud Autoencoders
  84. Cluster-based Kriging approximation algorithms for complexity reduction
  85. Automatic Configuration of Deep Neural Networks with Parallel Efficient Global Optimization
  86. Designing Ships Using Constrained Multi-objective Efficient Global Optimization
  87. A Novel Uncertainty Quantification Method for Efficient Global Optimization
  88. A multi-method simulation of a high-frequency bus line
  89. A new acquisition function for Bayesian optimization based on the moment-generating function
  90. Algorithm configuration data mining for CMA evolution strategies
  91. Time complexity reduction in efficient global optimization using cluster kriging
  92. A framework for evaluating meta-models for simulation-based optimisation
  93. Local subspace-based outlier detection using global neighbourhoods
  94. Towards Data Driven Process Control in Manufacturing Car Body Parts
  95. Fuzzy clustering for Optimally Weighted Cluster Kriging
  96. An Incremental Algorithm for Repairing Training Sets with Missing Values
  97. Analysis and Visualization of Missing Value Patterns
  98. Optimally Weighted Cluster Kriging for Big Data Regression
  99. Fitness Landscape Analysis of NK Landscapes and Vehicle Routing Problems by Expanded Barrier Trees