“…that make the optimization problems difficult to handle and can lead an optimizer to a suboptimal region in the search space. Simulated annealing, Monte-Carlo sampling, Stochastic tunneling, Parallel tempering, Stochastic Hill Climbing, PSO, GA, Evolution Strategies, Memetic Algorithms, Differential Evolution are some examples of stochastic algorithms [9,10,11,12,13,2,3,4,5,14,6,7,8,15]. Our focus in this review has been mainly on pure evolutionary computing techniques and their hybrids in which power of several methods are combined to produce a superior algorithm for global search.…”