Stochastic search algorithms that take their inspiration from nature are gaining a great attention of many researchers to solve high dimension and non -linear complex optimization problems for which traditional methods fails. Shuffled frog -leaping algorithm (SFLA) is recent addition to the family of stochastic search algorithms that take its inspiration from the foraging process of frogs. SFLA has proved its efficacy in solving discrete as well as continuous optimization problems. The present study introduces a modified version of SFLA that uses geometric centroid mutation to enhance the convergence rate. The variant is named as Centroid Mutated -SFLA (CM-SFLA). The proposal is implemented on five benchmark and car side impact problem. Simulated results illustrate the efficacy of the proposal in terms of convergence speed and mean value.

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A method to protect video contents from unauthorized access is known as a video encryption scheme. This paper first surveys the literature to identify most desired features of an encryption algorithm. Then a classification has been drawn according to their characteristics. After that, some of the algorithms are discussed and their working has been explained briefly. At the end a comparison has been shown displaying their performance on a few chosen parameters.