Abstract: For the uncertainty of parameters during flexible industrial process in the manufacturing workshops, a model of multi-objective fuzzy flexible job shop scheduling is established. To solve this model, the processing time, processing cost and material cost are described by triangular fuzzy numbers to minimize the makespan and production cost. An adaptive discrete flower pollination algorithm (ADMOFPA) is proposed. A discrete operator is utilized in the algorithm to discretize the solutions at the initialization period. To enhance the global exploration and local exploitation ability of ADMOFPA, an adaptive mutation operator is adopted. By simulating the instance of one flexible production workshop using the proposed algorithm, the results validate the effectiveness of the proposed algorithm compared with the basic FPA and particle swarm optimization.

Key words: multi-objective scheduling, fuzzy flexible job shop, triangular fuzzy numbers, flower pollination algorithm, production cost, discrete operator