The use of Genetic Algorithms (GA) in engineering has been growing during the last decades due to the fact that most engineering optimization problems are combinatorial and NP-hard. Most conventional methods of optimization deal with continuous variables, leading to designs mathematically feasible, but not necessarily practical. Genetic algorithms can deal with nixed design variable problem, complex design domain requirement, complex constraint equations as well as objective function and hence lead to optimal feasible design. In this paper we review literature using floating point genetic algorithm, variable chromosome length genetic algorithm, distributed genetic algorithm etc. Furthermore, we discuss certain approaches of GA which have been used by some researchers in design optimization and scheduling problems. In the end , along with some points regarding the strengths of GA, the difficulties which may arise in applying GA in different areas have also been discussed.