Examinando por Autor "Manuel Colmenar, Jose Manuel"

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    Multi-objective Optimization in Diversity Problems
    (Springer Nature, 2023-11-17) Manuel Colmenar, Jose Manuel; Herrán, Alberto; Martín-Santamaría, Raúl
    Diversity problems are usually studied from a single-objective point of view. However, two or more diversity functions could present opposite or divergent behavior, which requires a multi-objective point of view. To illustrate this kind of problems, this chapter presents the study of the bi-objective diversity problem (BODP), which considers the MaxSum and the MaxMin as objective functions to simultaneously maximize. Six different multi-objective algorithms have been described, analyzing their results on six performance metrics using a subset of instances from the MDPLIB 2.0 library.
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    WebGE: An Open-Source Tool for Symbolic Regression Using Grammatical Evolution
    (Springer Nature, 2022-04-15) Manuel Colmenar, Jose Manuel; Martín-Santamaría, Raúl; Hidalgo Pérez, José Ignacio
    Many frameworks and libraries are available for researchers working on optimization. However, the majority of them require programming knowledge, lack of a friendly user interface and cannot be run on different operating systems. WebGE is a new optimization tool which provides a web-based graphical user interface allowing any researcher to use Grammatical Evolution and Differential Evolution on symbolic regression problems. In addition, the fact that it can be deployed on any server as a web service also incorporating user authentication, makes it a versatile and portable tool that can be shared by multiple researchers. Finally, the modular software architecture allows to easily extend WebGE to other algorithms and types of problems.