Abstract:
Solving quadratic equation efficiently is a real-world challenge
nowadays, due to its wide applications in the task of determining a product's
profit, calculating areas or formulating the speed of an object. The general ap-
proach of finding the roots of a quadratic equation is not enough efficient due to
the requirement of high computation time. Because of the Genetic Algorithm's
stochastic characteristics and efficiency in solving problems it can be used to
find roots of quadratic equation precisely. In modern athletics reducing the
computation time of solving the quadratic equation has been so inevitable
where using a genetic algorithm can find a quick solution that doesn't violate
any of the constraints and with high precision also. Optimization has been done
in the Crossover and Mutation process which has reduced the number of itera-
tions for solving the equation. It reduces the time complexity of the existing
approach of solving the quadratic equation and reaches towards the goal effi-
cientl
