为解决企业在多个规划阶段内对不同类型设备的采购决策问题,考虑每个阶段产量的约束和不同类型设备的属性差异,以各阶段对不同类型设备采购数量为决策变量,总的采购费用和维护费用最小化为目标,构建混合整数规划模型。针对模型特点,设计一种与变邻域搜索方法相结合的混合遗传算法。提出基因组操作模式,利用多重随机方式生成初始种群,构造专门的遗传算子和染色体修复策略,实现对非线性、离散的多阶段动态决策问题的有效求解。算例结果验证了模型的正确性和算法的有效性,与其它算法相比,该算法具有更好的收敛速度和寻优能力。
To solve the enterprise procurement decision problems for different types of equipment over multi-period,a mixed integer programming model was constructed with consideration on production constraints in each period and the diversities in different types of equipment.The goal of this model was to minimize the total cost of purchase and maintenance of the equipment in different types,and the purchase amount of equipment was taken as decision variables.According to the characteristics of this model,a hybrid genetic algorithm integrating variable neighborhood search method was designed.The genome was addressed as an operation mode,and the initial population was generated through multiple random schemes,and the appropriate genetic operators and chromosome repair strategies were designed to handle the multi period dynamic decision problems with nonlinear and discrete properties effectively.An example was given to validate the correctness of the model and the effectiveness of the algorithm and the proposed algorithm has better performance on convergence speed and optimization capability than other algorithms.