Plant Genetics-Inspired Evolutionary Optimization: A Descriptive Tutorial

This chapter illustrates the characteristics of plant genetics-inspired evolutionary optimization (PGEO). The computation strategy of PGEO is inspired by the theory of Mendelian evolution. Presented PGEO optimizer is a binary-coded algorithm based on mainly three concepts from plant genetics: (i) the “denaturation” of DNA of two different species to produce the hybrid “offspring DNA,” (ii) the Mendelian evolutionary theory of genetic inheritance, which explains how the dominant and recessive traits appear in two successive generations, (iii) the epimutation, through which organism resists for natural mutation. The above concepts are reconfigured in order to design the binary meta-heuristic evolutionary training technique. Based on this framework, four evolutionary operators—(1) flipper, (2) pollination, (3) breeding, and (4) epimutation—are created in the binary domain. The chapter gives characteristics and a detailed tutorial to PGEO theory.

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