  The search for life outside the Solar System is an endeavour of astronomers
all around the world. With hundreds of exoplanets being discovered due to
advances in astronomy, there is a need to classify the habitability of these
exoplanets. This is typically done using various metrics such as the Earth
Similarity Index or the Planetary Habitability Index. In this paper, Genetic
Algorithms are used to evaluate the best possible habitability scores using the
Cobb-Douglas Habitability Score. Genetic Algorithm is a classic evolutionary
algorithm used for solving optimization problems. It is based on Darwin's
theory of evolution, "Survival of the fittest". The working of the algorithm is
established through comparison with various benchmark functions and extended
its functionality to Multi-Objective optimization. The Cobb-Douglas
Habitability Function is formulated as a bi-objective as well as a single
objective optimization problem to find the optimal values to maximize the
Cobb-Douglas Habitability Score for a set of promising exoplanets.
