Differential Search Algorithm (DSA) is a new and effective evolutionary algorithm for solving real-valued numerical optimization problems. DSA was inspired by migration of superorganisms utilizing the concept of brownian like motion. In , the problem solving success of DSA was compared to the successes of ABC, JDE, JADE, SADE, EPSDE, GSA, PSO2011 and CMA-ES algorithms for solution of numerical optimization problems.
DSA is a multi-strategy based, advanced evolutionary algorithm. DSA analogically simulates a superorganism that migrates between two stopovers. Standard DSA has four different search-methods; bijective-DSA (B-DSA), surjective-DSA (S-DSA), Elitist#1-DSA (E1-DSA), and Elitist#2-DSA (E2-DSA). Hybridization of DSA (H-DSA) search methods is quite easy.