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An Overview of Evolutionary Algorithms for Parameter Optimization
Abstract
Three main streams of evolutionary algorithms (EAs), probabilistic optimization algorithms based on the model of natural evolution, are compared in this article: evolution strategies (ESs), evolutionary programming (EP), and genetic algorithms (GAs). The comparison is performed with respect to certain characteristic components of EAs: the representation scheme of object variables, mutation, recombination, and the selection operator. Furthermore, each algorithm is formulated in a high-level notation as an instance of the general, unifying basic algorithm, and the fundamental theoretical results on the algorithms are presented. Finally, after presenting experimental results for three test functions representing a unimodal and a multimodal case as well as a step function with discontinuities, similarities and differences of the algorithms are elaborated, and some hints to open research questions are sketched.
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Citations
Cited by
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Trace is the Next AutoDiff: Generative Optimization with Rich Feedback, Execution Traces, and LLMs
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Model Swarms: Collaborative Search to Adapt LLM Experts via Swarm Intelligence
Feng, S., Wang, Z., Wang, Y., Ebrahimi, S., Palangi, H., Miculicich, L., Kulshrestha, A., Rauschmayr, N., Choi, Y., Tsvetkov, Y., et al. (2024) · arXiv · doi:10.48550/arxiv.2410.11163 · Cited by 24
“Inspired by Particle Swarm Optimization (Kennedy & Eber-hart, 1995) and evolutionary algorithms in general (B ¨ ack & Schwefel, 1993), M ODEL S WARMS employs several terminologies: • Each LLM expert, or “particle” in the model swarm, has a location represented by model weights; • Each particle has…”
EvoAgent: Towards Automatic Multi-Agent Generation via Evolutionary Algorithms
Yuan, S., Song, K., Chen, J., Tan, X., Li, D., & Yang, D. (2024) · arXiv · doi:10.48550/arxiv.2406.14228
Metadata
- Authors
- Bäck, T., & Schwefel, H.-P.
- Venue
- Evolutionary Computation
- Publisher
- MIT Press - Journals
- Published
- 1993-03
- Volume
- 1
- Issue
- 1
- Pages
- 1-23
- ISSN
- 1063-6560 (ISSN-L)
- 1530-9304
- OpenAlex
- W2020009149
- Cited by
- 2,111
- References
- 0
- FWCI
- 62.21
- Type
- journal article
- Language
- en
- Open access
- closed
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