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Benefiting from the flexible, scalable and secure environment, hybrid cloud can overcome the shortage of limited resources in private cloud to simultaneously execute large-scale scientific workflows. In hybrid cloud, privacy-sensitive tasks are not allowed to be executed on public resources, while non-sensitive tasks are unrestricted. As an NP-Complete problem, it is extraordinarily challenging to schedule multiple workflows efficiently, economically and energy-savingly under quality-of-service constraints. This paper models the hybrid-cloud-based privacy-aware multi-workflow scheduling as a tri-objective optimization problem that optimizes workflow-oriented total tardiness, private-cloud-oriented total energy consumption, and public-cloud-oriented total monetary cost. To the best of authors’ knowledge, few studies have been conducted on the tri-objective privacy-aware multi-workflow scheduling in hybrid cloud …