Abstract: A class of zero-wait fermentation process scheduling issues with batch process characteristics are researched. In order to solve the problem of easy deterioration in the process, a super heuristic difference algorithm is proposed, and the maximum makespan is minimized as the optimization goal. The algorithm is divided into two layers. The upper layer is an improved adaptive differential evolution algorithm to select and sort the heuristic operations in lower layer. The lower layer is combined and sorted into a new algorithm to operate on the problem domain, adding simulated annealing algorithm to avoid falling into local optimization. The method has a learning mechanism and the strong generalization ability for different problems. The effectiveness of the algorithm is verified by comparing with the actual production. The result shows that the algorithm has better performance than the traditional heuristic algorithm.

Key words: batch process, hyper-heuristic evolution algorithm, zero-wait, simulated annealing