The State of the Art in Cellular Evolutionary Algorithms

  • Alba E
  • Dorronsoro B
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Abstract

A person who never made a mistake never tried anything new. Albert Einstein (1879 -1955) – Physicist Before starting any new scientific research, it is necessary to know perfectly well the existing contributions to the considered field in the literature. This documentation step is basic for the right development of science, as it provides important knowledge of the working area, allowing us to take advantage of the contributions of others authors, and thus avoiding the development of low interest works as, for example, studies tackled before by other researchers. Hence, in this chapter we present a wide exploration of the state of art in cellular evolutionary algorithms, including and classifying some of the main existing publications related to this field. The chapter structure is detailed next. We start with Sect. 2.1 explaining the first appeared models of cEAs in the literature. In Sect. 2.2 the main the-oretical studies developed in cEAs are summed up, whereas Sect. 2.3 compiles some of the most relevant works where empiric studies of the functioning of cEAs have been carried out, and also comparisons to other models. A summary of the most important works contributing with algorithmic improvements to the cEAs field is shown in Sect. 2.4. Section 2.5 presents some works with high repercussion in the field of parallel cEAs. Finally, at the end of the chapter we summarize all this and mention some open research lines. 2.1 Cellular EAs: a New Algorithmic Model The cellular evolutionary algorithms were initially designed for working in massive parallel machines, composed of many processors executing simulta-neously the same instructions on different data (SIMD machines –Single In-struction Multiple Data) [88]. In the simplest case, the executed cEAs in this sort of machines used a single large population and assigned an only single individual to each processor. In order to avoid a high overload in communi-cations, the mating of the individuals was restricted to the closer individuals (that is, the ones belonging to their neighborhood).

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Alba, E., & Dorronsoro, B. (2008). The State of the Art in Cellular Evolutionary Algorithms (pp. 21–34). https://doi.org/10.1007/978-0-387-77610-1_2

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