Modified progressive random walk with chaotic PRNG

Abstract

In this paper, two modifications are proposed to the Progressive Random Walk (PRW) algorithm in order to address its potentially insufficient search space coverage. The first modification replaces the Pseudo-Random Number Generator (PRNG) with the uniform distribution by the chaotic map based PRNG for generating of the offset values and the second modification is called direction switching and is based on experiment observation. The modifications are implemented into the PRW and the resulting algorithm is called modified Progressive Random Walk. The search space coverage of the two algorithms is compared. Both algorithms are used in macro ruggedness estimation of the CEC2015 benchmark set and the results are discussed.