Abstract: There were many core components which could be remanufactured in automobile engine. Aiming at this problem, hybrid production programming model was established with automobile engine manufacturing and remanufacturing under uncertain environment. In this model, heterogeneous demands for new and remanufactured products were taken into account, and the demand for remanufactured products could be also satisfied by new products when the remanufactured products didn't satisfy self demand. The discrete scene of known probability was used to describe new products uncertainty of demand ratio, operation cost and remanufacturing product rate respectively, and uncertain description of remanufacturing rate was improved by stochastic chance constrained programming. Genetic algorithm for solving this model was presented, and a case was employed to verify the effectiveness and validity for model and solving method.

Key words: automobile engine, remanufacturing, lot sizing production planning, heterogeneous demand, uncertainty, genetic algorithms

摘要： 针对汽车发动机存在多个可再制造核心组件的特点，以需求满足率、运作成本和再制造产品率为运作目标，建立了不确定环境下的汽车发动机制造/再制造混合生产计划模型。该模型考虑了市场对新产品和再制造产品的异质需求，并且当再制造产品无法完全满足其自身需求时，可以由部分新产品来满足。分别采用已知概率的离散场景集合描述新产品市场需求、再制造产品市场需求和收回品数量的不确定性，并以随机机会约束规划对再制造率的不确定性描述进行了改进。给出了基于遗传算法的求解过程，并通过仿真实例验证了该计划模型和求解方法的有效性。

关键词: 汽车发动机, 再制造, 批量生产计划, 异质需求, 不确定性, 遗传算法