Pool-Based Genetic Programming Using Evospace, Local Search and Bloat Control

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@Article{juarez-smith:2019:MCA,

• author = "Perla Juarez-Smith and Leonardo Trujillo and Mario Garcia-Valdez and Francisco {Fernandez de Vega} and Francisco Chavez",
• title = "{Pool-Based} Genetic Programming Using Evospace, Local Search and Bloat Control",
• journal = "Mathematical and Computational Applications",
• year = "2019",
• volume = "24",
• number = "3",
• keywords = "genetic algorithms, genetic programming",
• ISSN = "2297-8747",
• URL = "https://www.mdpi.com/2297-8747/24/3/78",
• DOI = "doi:10.3390/mca24030078",
• abstract = "This work presents a unique genetic programming (GP) approach that integrates a numerical local search method and a bloat-control mechanism within a distributed model for evolutionary algorithms known as EvoSpace. The first two elements provide a directed search operator and a way to control the growth of evolved models, while the latter is meant to exploit distributed and cloud-based computing architectures. EvoSpace is a Pool-based Evolutionary Algorithm, and this work is the first time that such a computing model has been used to perform a GP-based search. The proposal was extensively evaluated using real-world problems from diverse domains, and the behaviour of the search was analysed from several different perspectives. The results show that the proposed approach compares favorably with a standard approach, identifying promising aspects and limitations of this initial hybrid system.",
• notes = "also known as \cite{mca24030078}",

}

Genetic Programming entries for Perla Sarahi Juarez-Smith Leonardo Trujillo Mario Garcia-Valdez Francisco Fernandez de Vega Francisco Chavez de la O

Citations