Cover Image

Drift Analysis with Fitness Levels for Elitist Evolutionary Algorithms

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	He, Jun, Zhou, Yuren
Format:	Preprint
Published:	2023
Subjects:	Neural and Evolutionary Computing
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Fast Estimations of Hitting Time of Elitist Evolutionary Algorithms from Fitness Levels
by: He, Jun, et al.
Published: (2023)

Estimate Hitting Time by Hitting Probability for Elitist Evolutionary Algorithms
by: He, Jun, et al.
Published: (2025)

Parent Selection Mechanisms in Elitist Crossover-Based Algorithms
by: Opris, Andre, et al.
Published: (2026)

Comparative Analysis of Evolutionary Algorithms for Energy-Aware Production Scheduling
by: Burmeister, Sascha C, et al.
Published: (2025)

A Fitness-assignment Method for Evolutionary Constrained Multi-objective Optimization
by: Ajani, Oladayo S., et al.
Published: (2023)

Runtime Analysis for Multi-Objective Evolutionary Algorithms in Unbounded Integer Spaces
by: Doerr, Benjamin, et al.
Published: (2024)

Theoretical and Empirical Analysis of Lehmer Codes to Search Permutation Spaces with Evolutionary Algorithms
by: Ma, Yuxuan, et al.
Published: (2025)

Large Language Models as Surrogate Models in Evolutionary Algorithms: A Preliminary Study
by: Hao, Hao, et al.
Published: (2024)

An Efficient Evolutionary Algorithm for Diversified Top-k (Weight) Clique Search Problems
by: Zheng, Jiongzhi, et al.
Published: (2024)

A First Look at Kolmogorov-Arnold Networks in Surrogate-assisted Evolutionary Algorithms
by: Hao, Hao, et al.
Published: (2024)

An Experimental Approach for Running-Time Estimation of Multi-objective Evolutionary Algorithms in Numerical Optimization
by: Huang, Han, et al.
Published: (2025)

An Efficient Evolutionary Algorithm for Few-for-Many Optimization
by: Shang, Ke, et al.
Published: (2026)

Optimizing Hearthstone Agents using an Evolutionary Algorithm
by: García-Sánchez, Pablo, et al.
Published: (2024)

Generalized Heavy-tailed Mutation for Evolutionary Algorithms
by: Eremeev, Anton V., et al.
Published: (2026)

Language Model Evolutionary Algorithms for Recommender Systems: Benchmarks and Algorithm Comparisons
by: Liu, Jiao, et al.
Published: (2024)

A First Running Time Analysis of the Strength Pareto Evolutionary Algorithm 2 (SPEA2)
by: Ren, Shengjie, et al.
Published: (2024)

Fitness and Overfitness: Implicit Regularization in Evolutionary Dynamics
by: Rappeport, Hagai, et al.
Published: (2025)

Self-Adjusting Evolutionary Algorithms Are Slow on Multimodal Landscapes
by: Lengler, Johannes, et al.
Published: (2024)

GEEvo: Game Economy Generation and Balancing with Evolutionary Algorithms
by: Rupp, Florian, et al.
Published: (2024)

Runtime Analysis for Permutation-based Evolutionary Algorithms
by: Doerr, Benjamin, et al.
Published: (2022)

Evolutionary Algorithm for Chance Constrained Quadratic Multiple Knapsack Problem
by: Perera, Kokila Kasuni, et al.
Published: (2025)

Multi-population GAN Training: Analyzing Co-Evolutionary Algorithms
by: Casas, Walter P., et al.
Published: (2025)

Near-Tight Runtime Guarantees for Many-Objective Evolutionary Algorithms
by: Wietheger, Simon, et al.
Published: (2024)

A Flexible Evolutionary Algorithm With Dynamic Mutation Rate Archive
by: Krejca, Martin S., et al.
Published: (2024)

Evolutionary Algorithms Are Significantly More Robust to Noise When They Ignore It
by: Antipov, Denis, et al.
Published: (2024)

All Constant Mutation Rates for the $(1+1)$ Evolutionary Algorithm
by: Kelley, Andrew James
Published: (2026)

Evolutionary Algorithms for Optimizing Emergency Exit Placement in Indoor Environments
by: Cotta, Carlos, et al.
Published: (2024)

Evolutionary Algorithms for Generating Graphs Matching Desired Laplacian Spectra
by: Richter, Hendrik, et al.
Published: (2026)

On Scalability of Multi-Objective Evolutionary Algorithms on Combinatorial Optimisation Problems
by: Tang, Menghao, et al.
Published: (2026)

Runtime Analysis of Single- and Multi-Objective Evolutionary Algorithms for Chance Constrained Optimization Problems with Normally Distributed Random Variables
by: Neumann, Frank, et al.
Published: (2021)

Optimized Drug Design using Multi-Objective Evolutionary Algorithms with SELFIES
by: Hömberg, Tomoya, et al.
Published: (2024)

A Comparison-Relationship-Surrogate Evolutionary Algorithm for Multi-Objective Optimization
by: Pierce, Christopher M., et al.
Published: (2025)

A Novel Dual-Stage Evolutionary Algorithm for Finding Robust Solutions
by: Du, Wei, et al.
Published: (2024)

Proven Advantage of Multiobjective Evolutionary Algorithms for Problems with Different Degrees of Conflict
by: Zheng, Weijie
Published: (2024)

Runtime Performance of Evolutionary Algorithms for the Chance-constrained Makespan Scheduling Problem
by: Shi, Feng, et al.
Published: (2022)

All Mutation Rates $c/n$ for the $(1+1)$ Evolutionary Algorithm
by: Kelley, Andrew James
Published: (2026)

An investigation on the use of Large Language Models for hyperparameter tuning in Evolutionary Algorithms
by: Custode, Leonardo Lucio, et al.
Published: (2024)

A Non-Dominated Sorting Evolutionary Algorithm Updating When Required
by: Farias, Lucas R. C., et al.
Published: (2025)

Interpreting Multi-objective Evolutionary Algorithms via Sokoban Level Generation
by: Zhang, Qingquan, et al.
Published: (2024)

A New Scope and Domain Measure Comparison Method for Global Convergence Analysis in Evolutionary Computation
by: Luo, Liu-Yue, et al.
Published: (2025)