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逆向物流回收车辆调度过程中,往往出现由于需求节点位置及需求量信息的不确定性导致难以合理决策完成回收任务所需派出回收车辆的数目,此时,第三方物流逐渐被应用于回收产品的运输服务中。然而在实际的回收过程中,通常各物流需求节点的需求量较小,需要对多个物流节点的产品集中后统一进行处理;同时由于外界因素的限制,不能保证任意两个节点间均存在可行路径,需要通过中转运输的方式寻找替代路线。针对以上问题,本文提出一种基于路径可行性与仓储集货运输模式的回收车辆路径设计方案,并根据问题的特点对传统蚁群算法(ACO)中编码方式以及概率选择操作方式进行改进,提出一种逆选择操作蚁群算法(ACO-nso)。最后通过算例证明提出模型与算法的有效性。
Reverse logistics recycling vehicle scheduling process, often due to the location of demand nodes and demand information uncertainty led to difficult to make a reasonable decision to complete the recovery tasks required to send the number of vehicles returned, this time, third-party logistics gradually being applied to the recovery of products Transportation service. However, in the actual recycling process, the demand of each logistics demand node is usually small, and the products of multiple logistics nodes need to be centrally processed and centralized. Due to the limitation of external factors, there is no guarantee that any two nodes exist viable Path, you need to find alternative routes by transit transport. In view of the above problems, this paper presents a design scheme of the reclaimed vehicle path based on the path feasibility and warehousing freight transportation mode, and improves the coding method and probability selection operation method of the traditional ACO according to the characteristics of the problem. An Inverse Selection Ant Colony Algorithm (ACO-nso). Finally, an example is given to show the effectiveness of the proposed model and algorithm.