In this paper, a unified differential evolution algorithm, named UDE, is presented for real parameter constrained optimization problems. The proposed UDE algorithm is inspired from some popular DE variants existing in the literature such as CoDE, JADE, SaDE, and ranking-based mutation operator. The primary feature of UDE lies in unifying the main idea of CoDE, JADE, SaDE, and ranking-based mutation. UDE uses three trial vector generation strategies and two parameter settings. At each generation, UDE divides the current population into two sub-populations. In the top sub-population, UDE employs all the three trial vector generation strategies on each target vector, just like in CoDE. For the bottom sub-population, UDE employs strategy adaptation, in which the trial vector generation strategies are periodically self-adapted by learning from their experiences in generating promising solutions in the top sub-population. Further, UDE utilizes a DE mutation strategy based local search operation. The constraints are handled in UDE using static penalty method. In contrast to most of the DE variants presented in the literature, UDE employs a generational replacement strategy. The proposed UDE algorithm is tested on the 28 benchmark problems provided for the CEC 2017 competition on constrained real parameter optimization. The experimental results demonstrate the efficacy of the presented algorithm in solving constrained real parameter optimization problems.