Cigarette Production Scheduling by Combining Workflow Model and Immune Algorithm

Cigarette production scheduling is vital in improving production efficiency and reducing supply delay. In this paper, a workflow model combined with an immune algorithm is proposed to solve this problem for improving production efficiency. First, the problem is formulated as a mixed-integer quadratically constrained programming model. Afterwards, the problem is transformed into a workflow resource allocation one. Based on this model, an immune algorithm is presented to find a set of activity priorities that are combined with dispatching rules to allocate resources. Activity priorities are represented by antibodies and evaluated by simulation runs on the workflow model. The proposed approach is applied to several production scheduling instances, and results are compared with other approaches. Experiments show that the result from the proposed approach is substantially better than those obtained from other approaches. It is demonstrated that our approach can effectively reduce production tardiness and improve efficiency.