An Immune Evolutionary Algorithm for Teacher/Class Timetabling Problem

The traditional evolutionary algorithm for teacher/class timetabling problem commonly evolves in a slow speed and trends to be stick to local optima. In this study, an immune-inspired evolutionary algorithm is proposed to solve the above problems. The algorithm utilizes the immune mechanisms including clonal selection, hypermutation, affinity evaluation, immune elimination and memory. The corresponding operators are designed. While the diversity is maintained, the convergence performance is improved by self-adaptive operators, such as clonal selection, hypermutation, crossover and mutation. Through the simulation experiments and comparative study, the algorithm is proved to be effective in solving the timetabling problem.