Pseudo-parallel genetic algorithm in process mining

Process mining is helpful for deploying new business processes as well as auditing, analyzing and improving the already enacted ones. An improved pseudo-parallel genetic algorithm is proposed with an asexual reproduction for avoiding crossover operators´ breach to nice gene patterns. The initial population is produced by greedy algorithm in order to enhance convergence velocity. Information exchange between subgroups employs island model in pseudo-parallel genetic algorithm. These measures are of great significance on reducing complexities and enhancing convergence velocity, as well as increasing global searching ability of the algorithm.