Differential Evolution: A review of more than two decades of research
Engineering Applications of Artificial Intelligence, ISSN: 0952-1976, Vol: 90, Page: 103479
2020
- 591Citations
- 361Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
Since its inception in 1995, Differential Evolution (DE) has emerged as one of the most frequently used algorithms for solving complex optimization problems. Its flexibility and versatility have prompted several customized variants of DE for solving a variety of real life and test problems. The present study, surveys the near 25 years of existence of DE. In this extensive survey, 283 research articles have been covered and the journey of DE is shown through its basic aspects like population generation, mutation schemes, crossover schemes, variation in parameters and hybridized variants along with various successful applications of DE. This study also provides some key bibliometric indicators like highly cited papers having citations more than 500, publication trend since 1996, journal citations etc. The main aim of the present document is to serve as an extended summary of 25 years of existence of DE, intended for dissemination to interested parties. It is expected that the present survey would generate interest among the new users towards the philosophy of DE and would also guide the experience researchers.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S095219762030004X; http://dx.doi.org/10.1016/j.engappai.2020.103479; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85079115456&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S095219762030004X; https://dx.doi.org/10.1016/j.engappai.2020.103479
Elsevier BV
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