中文摘要：

回收品质量、数量以及拆卸过程中的不确定性因素使再制造生产调度问题更加复杂。针对工件加工路径的可变性特点，建立了再制造生产中的job—shop调度模型，提出了一种基于可变长工序编码方法的改进遗传算法，设计了异常染色体的识别和重构方法，以及相应的遗传算子。在参数矩阵的指导下，该算法可以实现随机工序数目和随机工序顺序情况下再制造生产调度问题的优化求解。仿真实验证明了该算法的有效性和可行性。

英文摘要：

The uncertainties of quality, quantity and disassembly process of returns in remanufacturing cause additional complexity for its production scheduling. According to the variability of job process path, this paper proposed job-shop scheduling model for remanufactnring. In the model, put forward an improved genetic algorithm based on variable-length encode. Designed the GA operators and methods to identify chromosomes validity and reconstruct them. Under the guidance of parameters matrix, the algorithm could achieve the optimization solving for remanufacturing production scheduling with the random processing number and the random processing path of operations. The simulation results show that this algorithm is effective and feasible.