客户关系下的多仓库半开放式危险品运输路径优化

Multi-Depot Half-Open Hazardous Materials Transportation Routing Optimization Considering Customer Relationships

摘要:

在考虑客户关系的条件下，建立以运输总成本、运输风险和总延误时间最小化为目标的多仓库半开放式危险品运输路径优化模型，设计蚁群算法和模拟退火算法混合的蚁群?模拟退火（ACO-SA）嵌套算法求解该模型。该嵌套算法运用邻接矛盾矩阵表示客户关系，外层模拟退火算法负责修改危险品运输车辆与客户点的匹配关系，内层蚁群算法负责规划每辆车中具体的路径遍历顺序。将该嵌套算法应用于大小规模算例中，得到多个Pareto最优解，并与4种单一算法的求解结果进行比较，验证嵌套算法的有效性和可靠性。对比有无客户关系下两个算例的求解结果，证明客户间存在的合作或竞争关系将直接影响企业运输方案制定。

Abstract:

This paper proposes a multi-depot half-open hazardous materials transportation routing optimization model that incorporates customer relationships with the objectives of minimizing total transportation cost， transportation risk and total delay time. To solve the model， it designs an ant colony-simulated annealing （ACO‐SA）nested algorithm combining ant colony optimization algorithm （ACO） and simulated annealing algorithm （SA）. The nested algorithm uses an adjacency contradiction matrix to represent the customer relationships. The outer SA algorithm modifies the matching relationships between the hazardous materials transport vehicles and the customer points， while the inner ACO algorithm plans the specific path traversal sequence for each vehicle. The nested algorithm is tested on two examples to obtain multiple Pareto optimal solutions， which are then compared with the results of four single algorithms to validate the effectiveness and reliability of the nested algorithm. A comparison of the solution with and without considering customer relationships demonstrates that the existence of cooperative or competitive relationships between customers significantly affects the formulation of the enterprise’s transportation plan.