烟草物流配送系统韧性提升策略研究

Research on strategies for improving the resilience of tobacco logistics distribution systems

针对烟草物流配送系统在遭遇地震、洪水等破坏性强的突发事件时,其系统抗干扰和自修复能力不足等问题,首先,以车辆接替完成时刻、接替车辆完成配送的时间、运行水平响应值为约束条件,以最大化烟草物流配送系统韧性值为目标函数,构建烟草配送系统恢复优化模型.然后,设计自适应遗传算法求解该模型,并对算法中的自适应参数的取值进行了详细设置.最后,以某市烟草物流配送系统数据为例,验证恢复优化模型的有效性与不同恢复策略对系统韧性的影响.在算例中,设置包括1种随机攻击与两种目的攻击作为3种扰动情景,制定包括目标接替法、随机接替法、基于发车顺序的偏好接替法及基于车辆重要性的偏好接替法4种接替法确定恢复策略.研究结果表明:恢复优化模型是有效且稳定的,设计的自适应遗传算法具有收敛性;在3种扰动情景下,目标接替法提升系统韧性值的效果均优于其他3种接替法,使用自适应遗传算法求解恢复优化模型,烟草物流配送系统韧性值最高能够提升47%.

In response to the insufficient resilience,anti-interference and self-repair capabilities of tobacco logistics distribution systems during highly destructive emergencies such as earthquakes and floods,this study constructs an optimization model for enhancing the recovery of tobacco distribution systems.The model maximizes the resilience value of the system with constraints including vehicle replacement completion time,replacement vehicle completion time,and operational level response.An adaptive genetic algorithm is designed to solve this model,with detailed settings for adaptive parameters.Using data from a tobacco logistics distribution system in a specific city as a case study,the effectiveness of the recovery optimization model and the impact of different recovery strategies on system resilience are verified.The study considers three disturbance scenarios,which include one random attack and two purposeful attacks.It implements four replacement methods to determine optimal recovery strategies:target replacement,random replacement,preference-based on departure order,and preference-based on vehicle importance.Results indicate that the proposed recovery optimization model is effective and stable,with the adaptive genetic algorithm demonstrating convergence.Across the three disturbance scenarios,the target replacement method consistently outperforms the other strategies in enhancing system resilience.Applying the adaptive genetic algorithm to solve the recovery optimization model achieves a maximum resilience improvement of up to 47%for the tobacco logistics distribution system.