Modified Differential Evolution with Locality induced Genetic Operators for dynamic optimization.

•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.