Properties of robust solution searching in multi-dimensional space with genetic algorithms

A large number of studies on genetic algorithms (GAs) emphasize finding a globally optimal solution. Some other investigations have also been made for detecting multiple solutions. If a global optimal solution is very sensitive to noise or perturbations in the environment then there may be cases where it is not good to use this solution. We have proposed a new scheme, GA/RS³, which extends the application of GAs to domains that require the discovery of robust solutions and a mathematical model for this scheme has been developed restricting their search space to one-dimensional. We analyze properties of GAs/RS³ in multi-dimension search spaces. The effectiveness of the scheme is demonstrated by solving two-dimensional functions having broad and sharp peaks