Tight Runtime Bound for a (μ+1) GA on Jump_k with Realistic Crossover Probabilities
We provide a tight upper bound of O(μn log(k) + 4k/pc) for the runtime of a variant of the (μ+1) Genetic Algorithm on the Jump_k benchmark, under mild assumptions on the population size μ and crossover probability pc.
Differential Evolution with Parameter Control Methods for Efficient Mixed-Integer Black-Box Optimization
The performance of parameter control methods (PCMs) in differential evolution (DE) is crucial for efficient mixed-integer black-box optimization. The best PCM significantly depends on the combination of the mutation strategy and repair method used.
Moderate Population Sizes Provably Yield Strong Robustness to Noise in Evolutionary Algorithms
Moderate population sizes of at least logarithmic in the problem size are sufficient for the (1+λ) EA and (1,λ) EA to optimize the OneMax benchmark in the presence of constant bit-wise noise, without increasing the asymptotic runtime compared to the noiseless setting.
Evolving Benchmark Functions to Compare Evolutionary Algorithms via Genetic Programming
Using Genetic Programming to automate the creation of benchmark functions for comparing evolutionary algorithms.
MAP-Elites with Transverse Assessment for Multimodal Problems in Creative Domains: A Novel Approach to Multimodal Creative Tasks Using Quality Diversity Evolution
Quality Diversity evolution with MEliTA algorithm enhances multimodal creative tasks by promoting coherence and diversity in generated artefacts.
Rank-Based Learning and Local Model Based Evolutionary Algorithm for High-Dimensional Expensive Multi-Objective Problems
A novel Classifier-assisted rank-based learning and Local Model based multi-objective Evolutionary Algorithm (CLMEA) is proposed for high-dimensional expensive multi-objective optimization problems.
MAP-Elites with Transverse Assessment for Multimodal Problems in Creative Domains
The authors propose MEliTA, a variation of the MAP-Elites algorithm tailored for multimodal creative tasks, emphasizing coherence across modalities to improve text-to-image mappings within the solution space.
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