Study of the Influence of the Number Normalization Scheme Used in Two Chaotic Pseudo Random Number Generators Used as the Source of Randomness in Differential Evolution
원문 초록
In many publications, authors showed that chaotic pseudo random number generators (PRNGs) may improve performance of the evolutionary algorithms. In this paper, we use two chaotic maps Gingerbread man and Tinkerbell as the chaotic PRNGs instead of the classical PRNG in the differential evolution. Numbers generated by this maps are normalized to the unit interval by three different methods -- operation modulo, straightforward number normalization where we know minimal and maximal generated number and arctangent of the two variables $x$ and $y$, where numbers $x$ and $y$ are generated by the Gingerbread man map and Tinkerbell map. The first goal of this paper is to show whether the differential evolution convergence speed might be affected by the way how we normalize number generated by the chaotic map. The second goal is to find out the influence of the probability distribution function of the selected chaotic PRNGs. The results mentioned below showed that the selected normalization method may improve differential evolution convergence speed, especially in the case of arctangent and straightforward number normalization, where we know the minimal and maximal generated numbers.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Graph-Supported Dynamic Algorithm Configuration for Multi-Objective Combinatorial Optimization
Randomised Optimism via Competitive Co-Evolution for Matrix Games with Bandit Feedback
Benchmarking MOEAs for solving continuous multi-objective RL problems
Mergenetic: a Simple Evolutionary Model Merging Library
Evolutionary thoughts: integration of large language models and evolutionary algorithms
RainbowPlus: Enhancing Adversarial Prompt Generation via Evolutionary Quality-Diversity Search
토론
이 논문과 연결된 포럼 글이 아직 없습니다.