Simulated annealing is a computational algorithm for optimization. It mimics the physical process of thermal annealing in which a metal is heated and then slowly cooled to settle into a highly ordered crystal structure. For common metals, the lowest energy state is already known. But the method is useful for other problems where the best state is not known and exhaustively searching all possible states is impractical. The method is applied by modeling the problem as a physical system with structure, energy, and temperature. This Python module implements simulated annealing so that it can be easily applied to a variety of problems. An example program is include to perform simulated annealing of the traveling salesman problem.
OpenClass is a simple solution for class control. It provides multicast screen projection (sending the teacher's screen to all of the students), student attention requests (blocking student activities and asking them to look at teacher), viewing of all student screens at once, direct messaging to students, file and URL sharing, computer shutdown, access control for specific classes, and support for multi-seat configurations and multiple clients per machine. For students it provides automatic teacher discovery via broadcast, "raise hand" functionality, and automatic handling of network saturation and disconnection events.