基于改进免疫优化算法的物流仓库选址问题研究

Research on Logistics Warehouse Location Problem Based on Improved Immune Optimization Algorithm

对物流仓库选址进行合理规划,可降低企业的车辆运输成本与仓库成本。针对物流仓库选址的特点,建立有容量约束的物流仓库选址模型,模型中考虑了仓库的固定成本、车辆行驶成本和容量约束。针对物流仓库选址模型的特点,设计改进的免疫优化算法并进行求解,通过设计两种交叉算子与变异算子,提高免疫优化算法的邻域搜索能力;通过对算法中的参数进行灵敏度分析,选取最优参数组合方式,以提高算法性能。使用改进的免疫优化算法对案例进行求解,验证了模型的有效性。相较于CPLEX软件,改进的免疫优化算法在文中案例背景下可节约21.49s的计算时间。相较于经典免疫优化算法,改进的免疫优化算法可降低寻优迭代次数。结果表明,该算法可对设施选址问题进行有效求解。

The reasonable planning of logistics warehouse location can reduce the cost of vehicle transportation and warehouse.Accord⁃ing to the characteristics of warehouse location,a warehouse location model with capacity constraints is established.Fixed cost,vehi⁃cle running cost and capacity constraints are considered in the model.According to the characteristics of the model,an improved im⁃mune optimization algorithm is designed.Two crossover operators and mutation operators are designed to improve the neighborhood search ability of immune optimization algorithm.By analyzing the sensitivity of parameters in the algorithm,the optimal combination of parameters is selected to improve the performance of the algorithm.The improved immune optimization algorithm was used to solve the case and the validity of the model was verified.Compared with CPLEX software,the improved immune optimization algorithm can save 21.49s computing time under the background of the case.Compared with the classical immune optimization algorithm,the improved im⁃mune optimization algorithm can reduce the number of optimization iterations.The results show that the algorithm can effectively solve the facility location problem.