Differential Search Algorithm (DSA) for Numerical Optimization Problems
Pinar Civicioglu
civici@erciyes.edu.tr
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 [1], 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.
(code was updated on 03.April.2013, 23:00 GMT+3 )
1. P. Civicioglu, "Transforming Geocentric Cartesian Coordinates to Geodetic Coordinates by Using Differential Search Algorithm", Computers and Geosciences, 46, 229-247, 2012.
2. P. Civicioglu, E. Besdok, "A conceptual comparison of the cuckoo-search, particle swarm optimization, differential evolution and artificial bee colony algorithms", Artificial Intelligence Review, 39, 4, 315-346, 2013.
3. P. Civicioglu, "Backtracking Search Optimization Algorithm for numerical optimization problems", Applied Mathematics and Computation 219 (2013) 8121–8144.
