垃圾分类收运路径问题的新型混合蚁群算法求解

针对垃圾分类收运路径问题,考虑车辆装载容量约束、硬时间窗约束、装载率对成本的影响等条件下,以最小化运输成本和车辆固定成本为目标建立了数学模型。将考虑时间吻合度因子和车容量利用率因子的改进蚁群算法与混沌电磁场优化算法进行动态融合,并结合2-opt和两点交换的局部搜索方法,提出一种以改进蚁群算法为外部框架,混沌电磁场优化算法为内部模块的新型混合蚁群算法对城市生活垃圾分类收运问题进行求解。根据算法间优势互补的思想,利用两种算法的优点来弥补单个算法的缺陷,使其成功应用于该问题。最后,用车辆路径问题标准测试集和上海市杨浦区的数据作为实例进行测试与对比,验证了模型的正确性以及算法的有效性与优化能力。

Novel hybrid ant colony algorithm for solving problem of waste classification and transportation

This paper proposed the mathematical model with the goal of minimizing transportation costs and vehicle fixed costs which based on the urban waste classification collection and transportation problem,considering the vehicle loading capacity constraints,hard time window constraints,and the impact of loading rate on cost.Dynamic fusion of an improved ant colony algorithm that considered the time fit factor and the vehicle capacity utilization factor and chaotic electromagnetic field optimization algorithm,combined with 2-opt and two-point exchange local search method,this paper proposed a novel hybrid ant colony algorithm with improved ant colony algorithm as the external framework and chaotic electromagnetic field optimization algorithm as the internal module to solve the urban waste classification collection and transportation problem.According to the idea of complementary advantages between algorithms,using the advantages of the two algorithms to make up for the defects of a single algorithm,it successfully applied to this problem.Finally,it used the vehicle routing problem standard test set and data from Yangpu district,Shanghai as examples to test and compare,verifies the correctness of the model and the effectiveness and optimization capabilities of the algorithm.