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. REMAINING USEFUL LIFE IN COMPLEX MULTI-COMPONENT SYSTEMS: TAXONOMY, REVIEW, AND RESEARCH DIRECTIONS
  7. EvoCAD: Evolutionary CAD Code Generation with Vision Language Models
  8. Quality–diversity-driven robust evolutionary optimization of optical designs
  9. Development of a photonic crystal spectrometer for greenhouse gas measurements
  10. LLaMEA: Automatically Generating Metaheuristics with Large Language Models
  11. BLADE: Benchmark suite for LLM-driven Automated Design and Evolution of iterative optimisation heuristics
  12. Explainable Benchmarking for Iterative Optimization Heuristics
  13. Neighborhood Adaptive Differential Evolution
  14. Structural bias in optimization algorithms
  15. Optimizing Photonic Structures with Large Language Model Driven Algorithm Discovery
  16. Code Evolution Graphs: Understanding Large Language Model Driven Design of Algorithms
  17. Why Are You Wrong? Counterfactual Explanations for Language Grounding with 3D Objects
  18. Explainable Benchmarking for Iterative Optimization Heuristics
  19. In-the-loop Hyper-Parameter Optimization for LLM-Based Automated Design of Heuristics
  20. LLaMEA: A Large Language Model Evolutionary Algorithm for Automatically Generating Metaheuristics
  21. Surrogate-based automated hyperparameter optimization for expensive automotive crashworthiness optimization
  22. Stalling in Space: Attractor Analysis for Any Algorithm
  23. Controlling the Mutation in Large Language Models for the Efficient Evolution of Algorithms
  24. XAI for Benchmarking Black-Box Metaheuristics
  25. Explainable AI for Evolutionary Computation
  26. An Introduction to the Crossroads of Explainable Artificial Intelligence and Evolutionary Computation
  27. Global Sensitivity Analysis Is Not Always Beneficial for Evolutionary Computation: A Study in Engineering Design
  28. Leveraging Lightweight Generators for Memory Efficient Continual Learning
  29. ACO-NSGAII: A Novel Metaheuristics for Bi-Objective Electric Vehicle Routing Problems
  30. A Functional Analysis Approach to Symbolic Regression
  31. A Corridor Model Evolutionary Algorithm for Fast Converging Green Vehicle Routing Problem
  32. A Critical Analysis of Raven Roost Optimization
  33. Modular Optimization Framework for Mixed Expensive and Inexpensive Real-World Problems
  34. Hot off the Press: Parallel Multi-Objective Optimization for Expensive and Inexpensive Objectives and Constraints
  35. Landscape Analysis Based vs. Domain-Specific Optimization for Engineering Design Applications: A Clear Case
  36. Quality-diversity driven robust evolutionary optimization of optical designs
  37. Parallel multi-objective optimization for expensive and inexpensive objectives and constraints
  38. Generating Cheap Representative Functions for Expensive Automotive Crashworthiness Optimization
  39. A Deep Dive Into Effects of Structural Bias on CMA-ES Performance Along Affine Trajectories
  40. Evolutionary Computation and Explainable AI: A Roadmap to Understandable Intelligent Systems
  41. TX-Gen: Multi-Objective Optimization for Sparse Counterfactual Explanations for Time-Series Classification
  42. Towards Fairness in Machine Learning: Balancing Racially Imbalanced Datasets Through Data Augmentation and Generative AI
  43. Beyond the Veil of Similarity: Quantifying Semantic Continuity in Explainable AI
  44. Landscape-Aware Automated Algorithm Configuration Using Multi-output Mixed Regression and Classification
  45. Clustering-based Domain-Incremental Learning
  46. Curing ill-Conditionality via Representation-Agnostic Distance-Driven Perturbations
  47. New solutions to Cooke triplet problem via analysis of attraction basins
  48. DoE2Vec: Deep-learning Based Features for Exploratory Landscape Analysis
  49. Deep BIAS: Detecting Structural Bias using Explainable AI
  50. AI for Expensive Optimization Problems in Industry
  51. Application of Functional Kernel Hypothesis Testing for Channel Selection in Time Series Classification
  52. Evaluation of deep unsupervised anomaly detection methods with a data-centric approach for on-line inspection
  53. BBOB Instance Analysis: Landscape Properties and Algorithm Performance Across Problem Instances
  54. Challenges of ELA-Guided Function Evolution Using Genetic Programming
  55. A data-centric approach to anomaly detection in layer-based additive manufacturing
  56. Evolutionary Algorithms for Parameter Optimization—Thirty Years Later
  57. The Opaque Nature of Intelligence and the Pursuit of Explainable AI
  58. Multi-surrogate Assisted Efficient Global Optimization for Discrete Problems
  59. BIAS: A Toolbox for Benchmarking Structural Bias in the Continuous Domain
  60. GSAreport: Easy to Use Global Sensitivity Reporting
  61. A Comparison of Global Sensitivity Analysis Methods for Explainable AI with an Application in Genomic Prediction
  62. A Comparison of Global Sensitivity Analysis Methods for Explainable AI with an Application in Genomic Prediction
  63. Analysis of how bias in search algorithms can affect the search behaviour
  64. Exploratory Landscape Analysis in Real-World Engineering Optimization
  65. Multi-point acquisition function for constraint parallel efficient multi-objective optimization
  66. End-to-End Pipeline for Uncertainty Quantification and Remaining Useful Life Estimation: An Application on Aircraft Engines
  67. Explainable Artificial Intelligence for Exhaust Gas Temperature of Turbofan Engines
  68. Constrained Multi-Objective Optimization with a Limited Budget of Function Evaluations
  69. Multitask Shape Optimization Using a 3-D Point Cloud Autoencoder as Unified Representation
  70. Optimally Weighted Ensembles for Efficient Multi-objective Optimization
  71. Analysis of Structural Bias in Differential Evolution Configurations
  72. A Comparison of many Global Sensitivity Analysis methods
  73. Exploiting Generative Models for Performance Predictions of 3D Car Designs
  74. Using Machine Learning to Detect Rotational Symmetries from Reflectional Symmetries in 2D Images
  75. Point2FFD: Learning Shape Representations of Simulation-Ready 3D Models for Engineering Design Optimization
  76. BIAS: A Toolbox for Benchmarking Structural Bias in the Continuous Domain
  77. BIAS: A Toolbox for Benchmarking Structural Bias in the Continuous Domain
  78. Emergence of structural bias in differential evolution
  79. Exploiting Local Geometric Features in Vehicle Design Optimization with 3D Point Cloud Autoencoders
  80. SAMO-COBRA: A Fast Surrogate Assisted Constrained Multi-objective Optimization Algorithm
  81. Requirements towards optimizing analytics in industrial processes
  82. A Tailored NSGA-III for Multi-objective Flexible Job Shop Scheduling
  83. Back To Meshes: Optimal Simulation-ready Mesh Prototypes For Autoencoder-based 3D Car Point Clouds
  84. Neural Network Design: Learning from Neural Architecture Search
  85. Improving NSGA-III for flexible job shop scheduling using automatic configuration, smart initialization and local search
  86. Feature Visualization for 3D Point Cloud Autoencoders
  87. A New Approach Towards the Combined Algorithm Selection and Hyper-parameter Optimization Problem
  88. On the Efficiency of a Point Cloud Autoencoder as a Geometric Representation for Shape Optimization
  89. Scalability of Learning Tasks on 3D CAE Models Using Point Cloud Autoencoders
  90. Cluster-based Kriging approximation algorithms for complexity reduction
  91. Automatic Configuration of Deep Neural Networks with Parallel Efficient Global Optimization
  92. Designing Ships Using Constrained Multi-objective Efficient Global Optimization
  93. A Novel Uncertainty Quantification Method for Efficient Global Optimization
  94. A multi-method simulation of a high-frequency bus line
  95. A new acquisition function for Bayesian optimization based on the moment-generating function
  96. Algorithm configuration data mining for CMA evolution strategies
  97. Time complexity reduction in efficient global optimization using cluster kriging
  98. A framework for evaluating meta-models for simulation-based optimisation
  99. Local subspace-based outlier detection using global neighbourhoods
  100. Towards Data Driven Process Control in Manufacturing Car Body Parts
  101. Fuzzy clustering for Optimally Weighted Cluster Kriging
  102. An Incremental Algorithm for Repairing Training Sets with Missing Values
  103. Analysis and Visualization of Missing Value Patterns
  104. Optimally Weighted Cluster Kriging for Big Data Regression
  105. Fitness Landscape Analysis of NK Landscapes and Vehicle Routing Problems by Expanded Barrier Trees