A Model Based on Genetic Algorithm for Solving Polynomial Equations

A model has been developed that effectively solves polynomial equations by leveraging and enhancing the genetic algorithm, combined with concepts from the bisection method used in numerical computations. Unlike traditional methods, this approach eliminates the need to specify an initial interval to locate the root, making it more versatile and efficient. The model intelligently searches for the root through an adaptive process that mimics evolutionary principles, such as selection, crossover, and mutation, which allows it to converge on a solution without predefined bounds. This innovative method is not limited to purely mathematical problems but extends its applicability to various fields, including physics, surveying, and data structure optimization. By removing the dependence on initial intervals, the model offers a more robust solution for complex equations, providing a valuable tool for researchers and professionals working in diverse scientific disciplines. The adaptability and broad applicability of this model make it a significant advancement in the field of root-finding algorithms.