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A new manufacturing paradigm, i.e. Cloud Manufacturing (CMfg) has been proposed recently. In order to satisfy high efficiency and low cost collaborative design task scheduling in CMfg, a new energy adaptive immune genetic algorithm (EAIGA) was designed. With the introduction of potential energy storage and detection, the new algorithm can not only improve searching diversity based on immune strategy, but also adaptively adjust the probabilities of crossover and mutation with low time complexity. The experimental results demonstrate that the new algorithm can effectively solving collaborative design task scheduling problem with a good balance between searching diversification and intensification.