A new hybrid algorithm for modeling of flow shop scheduling : Bird mating optimizer based on GA

For flow shop multi-objective scheduling optimization problem, combining the theory of genetic evolution and mutation factor analysis method, a hybrid algorithm of BMO is proposed. Genetic evolution and mutation factor is used to calculate fitness value, improving the search performance of the algorithm. The method is a collection of multiple scheduling process as a flock, by simulating the birds breeding progeny with excellent gene optimization to solve the three targets flow shop scheduling problem. Finally the shop scheduling test case on the MATLAB platform experiment, is able to get uniform distribution of Pareto front, the solutions of the proposed algorithm is verified better than other algorithms.