Applications of Evolutionary Computation

.- Evolutionary machine learning.

.- Social Interpretable Reinforcement Learning.

.- Into the Black Box: Mining Variable Importance with XAI.

.- Evolving RNNs for Stock Forecasting: A Low Parameter Efficient Alternative to Transformers.

.- Generate more than one child in your co-evolutionary semi-supervised learning GAN.

.- EDCA - An Evolutionary Data-Centric AutoML Framework for Efficient Pipelines.

.- 30 years of particle swarm optimisation.

.- Proposal of Efficient Particle Swarm Optimization for Constrained Optimization Problems.

.- A Survey of Modern Hybrid Particle Swarm Optimization Algorithms.

.- An Investigation of Structural Bias in Particle Swarm Optimization.

.- GPSO in PTO.

.- We are Sending you Back... to the Optimum! Fuzzy Time Travel Particle Swarm Optimization.

.- Memetic Variations of Overlapping Swarm Intelligence.

.- Analysis of Evolutionary Computation Methods: Theory, Empirics, and Real-World Applications.

.- Multi-Tree Genetic Programming for Large-scale Dynamic Tugboat Scheduling.

.- Bio-inspired Algorithms for Green Computing and Sustainable Complex Systems.

.- Hybridization of techniques based on Genetic Algorithms and Neural Networks to determine the water requirements of fig trees.

.- Evaluating the Impact of Hysteretic Phenomena and Implementation Choices on Energy Consumption in Evolutionary Algorithms.

.- Measuring energy consumption of BBOB fitness functions.

.- Computational Intelligence for Sustainability.

.- A PSO-based MPPT with Dynamic Monitoring Reset for PV Systems.

.- An innovative approach for managing the water requirements of fig trees using artificial intelligence.

.- GPBus: Genetic Programming based Automated Machine Learning for Bus Delay Prediction.

.- Improving Fairness in Allocation of Emergency Medical Services using Multi-Objective Evolutionary Optimization.

.- A Multi-Agent System for Optimal Train Scheduling in Single-Track Railways.

.- EvoLLMs (Integrating Evolutionary Computing with Large Language Models (LLMs).

.- Evolutionary Bias Identification with Embeddings.

.- Probing LLMs on Optimization Problems: Can They Recall and Interpret Problem Features?.

.- Open and Closed-source Models for LLM-generated Metaheuristics Solving Engineering Optimization Problem.

.- Beyond the Hype: Benchmarking LLM-Evolved Heuristics for Bin Packing.

.- Controlling the Mutation in Large Language Models for the Efficient Evolution of Algorithms.

.- Evolutionary Computation in Edge, Fog, and Cloud Computing.

.- A Communication-aware and Energy-efficient Genetic Programming based Method for Dynamic Resource Allocation in Clouds.

.- A Genetic Algorithm-Based Parameter Selection for Communication Efficient Federated Learning.

.- Evolutionary Computation in Image Analysis, Signal Processing, and Pattern Recognition.

.- Evolving Cellular Automata with Function-Based Conditional Rules for Image Filtering.

.- Machine Learning and AI in Digital Healthcare and Personalized Medicine.

.- Addressing Radiotherapy Scheduling with a Bin Packing Problem Formulation: A Comparative Study of Exact Solvers and Genetic Algorithms.

.- A Symbolic Regression Screening Approach within Peptide Optimisation.

.- Estimation of total body fat using symbolic regression and evolutionary algorithms.

.- Soft Computing Applied to Games.

.- Injecting Combinatorial Optimization into MCTS: Application to the Board Game boop.

.- Robust search for the underlying objectives in black-box games with binary outcomes.