不确定处理时间批处理过程的鲁棒调度新策略

针对化工批处理调度过程中处理时间不确定的问题,建立了具有分解结构的调度模型,提出了一种新的鲁棒调度策略.策略由基本调度策略和在线调整两部分组成,分别与模型的主问题和子问题相对应.提出了基于遗传算法的分解算法求解模型,以获取具有鲁棒性和最优性的基本调度策略.通过对子问题的分析,提出了运用简单的推理进行在线调整的方法,无需复杂计算,并运用动态规划的原理说明了该方法的可行性和最优性.最后用实例说明了该鲁棒调度策略的有效性.

Novel Robust Scheduling Strategy for Batch Process with Uncertain Processing Time

For batch chemical processes with uncertain processing time,a novel robust scheduling strategy is proposed.The strategy is composed of the basic scheduling strategy and the on-line adjusting method.First,a novel mathematic scheduling model with decomposition structure is proposed.The master problem of the model corresponds to the basic scheduling strategy and the sub problem corresponds to on-line adjusting method.Then a decomposition algorithm based on genetic algorithm is proposed to solve the model and to find the optimal basic strategy.After analyzing the sub problem,the on-line adjusting method based on simple deduction is given,and the feasibility and optimality of this method are also explained using dynamic programming.Finally an example is presented to illustrate the effectiveness of this method.