One of the most effective methods for solving optimal control problems with mixed constraints is a continuation method for optimal trajectories. This method, unlike the direct methods, allows you to track the qualitative features of the behavior of optimal trajectories, which is especially important when solving applied tasks.
The report discusses common problems associated with the automation of scientific and engineering computations, as well as promising approaches to solving these problems, based on cloud computing models. The use of service-oriented approach in scientific and engineering computing can improve the research productivity by enabling publication and reuse of computing applications, as well as creation of cloud services for automation of computation processes. An implementation of this approach is presented in the form of Everest cloud platform which supports publication, execution and composition of computing applications in a distributed environment.
The complexity of high-performance computing infrastructures and applications require the use of problem-oriented interfacesand automation of basic activities in order to support the solving of complex scientific and engineering problems. The use of service-oriented approach and cloud computing models can improve the research productivity by enabling publication and reuse of computing applications, as well as creation of cloud services for automation of computations. The paper describes the implementation of this approach in the form of a web-based platform following the Platform as a Service model. Unlike other solutions, the presented Everest platform runs applications on external computing resources connected by users, implements flexible binding of resources to applications and provides an open programming interface.