ECF: A C++ framework for evolutionary computation

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@Article{JAKOBOVIC:2024:softx,

• author = "Domagoj Jakobovic and Marko Durasevic and Stjepan Picek and Bruno Gasperov",
• title = "{ECF:} A C++ framework for evolutionary computation",
• journal = "SoftwareX",
• year = "2024",
• volume = "27",
• pages = "101640",
• keywords = "genetic algorithms, genetic programming, Evolutionary computation, C++, Artificial intelligence, Metaheuristics",
• ISSN = "2352-7110",
• URL = "https://www.sciencedirect.com/science/article/pii/S2352711024000116",
• DOI = "doi:10.1016/j.softx.2024.101640",
• code_url = "http://ecf.zemris.fer.hr/html/index.html",
• code_url = "https://github.com/ElsevierSoftwareX/SOFTX-D-23-00449",
• size = "7 pages",
• 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

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