We present a modified Differential Evolution (DE) for dynamic optimization.
The modified DE mutation can retain the proximity information for each solution.
A local-best crossover operation helps in preserving diversity.
We propose an exhaustive dynamic change detection technique.
Our algorithm has been extensively tested and validated w.r.t. the state-of-the-art.