Hybridizing fast taboo search with ant colony optimization algorithm for solving large scale permutation flow shop scheduling problem

In order to solve the time over-consuming problem caused by max-min ant system (MMAS) for solving large scale permutation flow shop scheduling problem (PFSP), a hybrid ant colony algorithm is proposed by incorporating the MMAS with taboo search algorithm based on PFSP´s block properties. The new algorithm can reduce neighborhood by eliminating quantity of inferior solutions and can enhance global optimization ability by applying taboo search algorithm. Results of experiments on larger scale PFSP instances show that TB-MMAS obviously reduces the calculation time and effectively eliminates the premature convergence compared with MMAS.