ECF: A C++ framework for evolutionary computation
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- @Article{JAKOBOVIC:2024:softx,
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author = "Domagoj Jakobovic and Marko Durasevic and
Stjepan Picek and Bruno Gasperov",
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title = "{ECF:} A C++ framework for evolutionary computation",
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journal = "SoftwareX",
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year = "2024",
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volume = "27",
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pages = "101640",
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keywords = "genetic algorithms, genetic programming, Evolutionary
computation, C++, Artificial intelligence,
Metaheuristics",
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ISSN = "2352-7110",
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URL = "https://www.sciencedirect.com/science/article/pii/S2352711024000116",
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DOI = "doi:10.1016/j.softx.2024.101640",
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code_url = "http://ecf.zemris.fer.hr/html/index.html",
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code_url = "https://github.com/ElsevierSoftwareX/SOFTX-D-23-00449",
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size = "7 pages",
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abstract = "Metaheuristics have been shown to be efficient
techniques for addressing a wide range of complex
optimization problems. Developing flexible, reliable,
and efficient frameworks for evolutionary computation
metaheuristics is of great importance. With this in
mind, ECF - Evolutionary Computation Framework, a
versatile open-source framework for evolutionary
computation written in C++, was developed. In addition
to a wide range of efficiently implemented algorithms,
it offers a variety of genotypes, parallelism with MPI,
plug-and-play components, predefined problems, a
configurable environment, as well as seamless
integration between its components. By combining
user-friendliness and customizability, ECF caters to
both novice users and experienced practitioners. Its
versatility has been demonstrated through extensive
applications to various continuous and combinatorial
optimization problems. This paper delves into the
framework's key features, provides practical usage
examples, highlights the impact of ECF, and outlines
the plans for its future development",
- }
Genetic Programming entries for
Domagoj Jakobovic
Marko Durasevic
Stjepan Picek
Bruno Gasperov
Citations