To efficiently address the multi-order-per-job (MOPJ) scheduling problem of a single machine with multiple preprocess constraints in wafer fabrications, including setup time, uncertain allocation of front opening unified pods(FOUPs), machine parameter adjustment, a scheduling problem domain was described and a mathematical programming model was set up with an objective of minimizing total completion time, and several theorems were established to obtain superior feasible solutions, in addition, a hybrid invasive weed optimization algorithm combined with differential evolution and adopted a two-level encoding mechanism was developed, in which the learning mechanism was introduced to enhance the quality of the solution. Moreover, adaptive process was applied to the mutation and neighborhood search to effectively improve the algorithm convergence. Finally, simulation results verify the validness and feasibility of the proposed algorithm and show that a 10% improvement is made on the performance by the scheduling approach.