基于动态规划的炼厂多阶段生产调度模型的建立及求解

针对炼厂生产随时间变化的诸多因素,建立了市场需求不确定下的炼厂多阶段生产调度动态规划模型。以各阶段产品产量为决策变量,各阶段库存为状态变量,阶段收益为目标。由于模型中存在不等式约束,一般的动态规划求解方法很难求解,提出用动态规划-混合遗传算法求解,最后给出实例计算,其结果验证了该模型的适用性和算法的有效性。

A Dynamic Programming Model for Multistage Production Planning of a Refinery Plant

On account of the time-varying factors, a dynamic programming model with multistage production planning on uncertain demand was addressed with the profits as objective function and mass balance, equipment processing capacity quality demand, tank capacity, energy consumption and inventory as constraints. The decision variables were the production of the refinery product in multistage and the state variables were inventory. Because of the ine- quality constraints, ordinary method for solving dynamic programming was unsuitable, thus a hybrid genetic algorithm was used for this problem. At last, a calculating example is given, and the validity of the model is verified.