All Stories

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