All Stories

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