We propose an adaptive DE algorithm for unconstrained optimization problems.

Symmetric Latin hypercube design is employed to initialize the population.

Trial vector generation strategy adaptation is introduced.

Control parameters adaptation is introduced.

Experimental results show that SLADE is better than other DE algorithms.