Towards a CRISPR Cas9 Enhanced Genetic Algorithm

Clustered regularly interspaced palindromic repeats (CRISPR) is an adaptive immune system used by microbes to defend themselves against virus or bacteriophage attacks. In a nutshell, this technique creates an array of virus DNA which acts as a genomic record of previous viral attacks. Along with CRISPR associated protein 9 (Cas9), bacteria use the CRISPR array to identify and cleave viral DNA during future attacks. In medicine, agriculture, and biotechnology, CRISPR Cas9 has been studied as a revolutionary gene editing system that can target specific sequences in a genome with high accuracy. The field of Evolutionary Algorithms (EAs) uses biological evolution and inspiration from genetics to encode an optimization problem's candidate solution as a genome. Genetic modifications are then applied to improve candidate solutions to a global optima. As such, EAs can be viewed as techniques that utilize genetic editing to achieve the desired target, i.e. a solution. Accordingly, this paper proposes CRISPR techniques to identify the building blocks of a solution, and then applies Cas9 for precise insertion in a candidate solution. In the reported work, a genetic algorithm (GA) is enhanced using CRISPR Cas9 techniques on knapsack problems with increasing difficulty. The achieved results are compared to those of a standard GA and estimation of distribution algorithm (EDA). The results show that CRISPR Cas9 enhanced GA (CRISPR GA) is a suitable technique for optimization problems, as it correctly identifies building blocks and performs gene modifications that lead to high quality results.