A disruptive technology fundamentally transforming the way that computing services are delivered, cloud computing offers information and communication technology users a new dimension of convenience of resources, as services via the Internet. Because cloud provides a finite pool of virtualized on-demand resources, optimally scheduling them has become an essential and rewarding topic, where a trend of using Evolutionary Computation (EC) algorithms is emerging rapidly. Through analyzing the cloud computing architecture, this survey first presents taxonomy at two levels of scheduling cloud resources. It then paints a landscape of the scheduling problem and solutions. According to the taxonomy, a comprehensive survey of state-of-the-art approaches is presented systematically. Looking forward, challenges and potential future research directions are investigated and invited, including real-time scheduling, adaptive dynamic scheduling, large-scale scheduling, multiobjective scheduling, and distributed and parallel scheduling. At the dawn of Industry 4.0, cloud computing scheduling for cyber-physical integration with the presence of big data is also discussed. Research in this area is only in its infancy, but with the rapid fusion of information and data technology, more exciting and agenda-setting topics are likely to emerge on the horizon. Categories and Subject Descriptors: I.2.8 [Artificial Intelligence]: Problem Solving, Control Methods, and Search—Heuristic methods; G.1.6 [Numerical Analysis]: Optimization—Global optimization; D.4.1 [Process Management]: Scheduling; H.3.5 [Online Information Services]: Web-based Services; Commercial Services; H.3.4 [Systems and Software]: Distributed Systems; Performance Evaluation; C.1.4 [Parallel Architectures]: Distributed Architectures; C.2.1 [Network Architecture and Design]: Network Communications; Network Topology; Wireless Communication; C.2.3 [Network Operations]: Network Management; Network Monitoring; C.5.5 [Servers]; K.1 [The Computer Industry]: Suppliers