Scheduling of Uncertain Multi-product Batch Processes Under Finite Intermediate Storage Policy

Abstract

There are various uncertainties in the production scheduling of the real-world applications. And in multi-product batch processes, the intermediate storage often can be used to increase plant productivity and operational efficiency. In this paper, the scheduling mathematical model for multi-product batch processes under Finite Intermediate Storage (FIS) policy with uncertain processing time has been established based on fuzzy programming theory. And the Maximum Membership Functions of Mean Value method is applied to convert the fuzzy scheduling model to the general optimization model. Furthermore, a fuzzy immune scheduling algorithm combined with the feature of the Immune Algorithm is proposed, which can prevents the possibility of stagnation in the iteration process and achieves fast convergence for global optimization. The effectiveness and efficiency of the fuzzy scheduling model and the proposed algorithm are demonstrated by simulation results.