Constrained Single-Objective Optimization Using Differential Evolution

Differential evolution (DE) is a rather new evolutionary optimization algorithm that has been shown to be fast and simple for unconstrained single-objective optimization problems. In this work DE is employed for the constrained optimization test suite of the special session on constrained real parameter optimization at CEC06. Constraints are handled using a modified selection procedure that does not require additional parameters. For the control parameters of the DE algorithm the best found settings from another examination were used so that almost no parameter tuning was necessary. Most of the test functions are successfully and reliably optimized. Difficulties arise mainly from a high number of equality constraints.