Research on Complex Curriculum Arrangement Problem Based on Novel Quantum Genetic Evolutionary Algorithm
LIU Shuguang, Lin Ba · 2019
Scheduling problem in Colleges and universities has always been a concern of many people. The essence of course scheduling is to allocate courses, teachers and students to the appropriate classroom in the appropriate time period, which involves many factors. This is a multi-objective scheduling problem, which is called timetable problem in operational research. Quantum Genetic Algorithm (QGA), which originates from the organic integration of quantum computing and genetic algorithms, has the advantages of outstanding ability to seek optimal solutions, faster computing speed and smaller overall computing scale, and can solve multi-objective scheduling or optimization problems well. In this paper, the QGA's principle, method and basic flow is introduced, the constraints of the complex curriculum arrangement problem is discussed, and a method to solve the problem of course scheduling in colleges and universities by using this advanced algorithm is also given. The experimental result shows that the quantum genetic evolutionary algorithm is much better than the genetic algorithm, and the optimization results are ideal.