Scheduling problems is a form of decision-making that allocates limited resources to tasks and its goal is to optimize one or more objectives. It exists widely in most of the modern manufacturing and production industries. As a expansion of classic flow shop scheduling problem

hybrid flow shop scheduling problem is closer to the practical production process. This paper presents an improved biogeography optimization algorithm(IBBO) to solve hybrid flow shop scheduling problem. By introducing improved strategy

enhance the ability of global and local search and improve the convergence speed. Simulation experiments based on ten standard scheduling instances and comparison with genetic algorithm verify the excellence of the improved biogeography-based optimization algorithm in solving hybrid flow shop scheduling problem.