Abstract
This chapter describes a chaos based random walk (CRW) algorithm for analyzing landscape structure in continuous search spaces. Unlike the existing random walks, no fixed step size is required in the proposed algorithm, rather conduct the random walk. The chaotic map is used to generate the chaotic pseudo random numbers (CPRN) for determining the variable-scaled step size and direction. The superiority of the new method has been demonstrated while comparing it with the simple and progressive random walk algorithms using histogram analysis. The performance of the proposed CRW algorithm is evaluated on the IEEE Congers on Evolutionary Computation (CEC) 2013 benchmark functions in continuous search space having different levels of complexity. The proposed method is applied to analyzing the landscape structure for protein structure prediction problem in continuous search space.
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