Evolutionary algorithms: A critical review and its future prospects

By Pradnya A. Vikhar. International Conference on Global Trends in Signal Processing, Information Computing and Communication, 2016

403 citations recorded by the source corpus.

Subfields: Artificial Intelligence

View Paper: https://www.semanticscholar.org/paper/9c4b8f3b53067a34cc13e8b5b3d54071327a1388

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Koushik Sen
2. Cody Hao Yu
3. Daniela Fogli
4. Lianmin Zheng
5. Elena Casiraghi
6. Barbara Rita Barricelli
7. Joseph E. Gonzalez
8. Ion Stoica

Citations in the corpus

• Ansor : Generating High-Performance Tensor Programs for Deep Learning (2020, background): “Evolutionary search [54] is a generic meta-heuristic algorithm inspired by biological evolution.”
• A Survey on Digital Twin: Definitions, Characteristics, Applications, and Design Implications (2019, methodology): “Evolutionary algorithms [104], or stochastic optimization [59] may be used for choosing the parameter settings producing the best fit between the DT and its twin.”