基于累积前景理论的物流配送干扰管理问题研究  

Study on Disruption Management Problem for Logistics Distribution based on Cumulative Prospect Theory

作　　者：张鹏[1] 石莎莎 宁涛 ZHANG Peng;SHI Shasha;NING Tao(Innovation Entrepreneurship Institute of Education,Dalian Jiaotong University,Dalian 116028,China;Software Institute,Dalian Jiaotong University,Dalian 116054,China;College of Computer Science and Engineering,Dalian Minzu University,Dalian 116600,China)

机构地区：[1]大连交通大学创新创业教育学院,辽宁大连116028 [2]大连交通大学软件学院,辽宁大连116054 [3]大连民族大学计算机科学与工程学院,辽宁大连116600

出　　处：《大连交通大学学报》2021年第4期94-100,共7页Journal of Dalian Jiaotong University

基　　金：国家自然科学基金重点资助项目(71531002,71471025);辽宁省自然科学基金资助项目(20180550499,2019-ZD-0109);辽宁省教育厅科学研究计划资助项目(JDL2019022)。

摘　　要：在实际物流配送中,客户时间窗的变化经常导致配送方案的改变,而对其他客户满意度造成的影响.为此,提出累积前景理论,建立了价值函数和概率权重的乘积来衡量客户的满意度,并运用干扰管理的思想,设计了扰动最小的干扰策略和扰动恢复模型.同时,提出一种改进的自适应蚁群算法,改进了蚂蚁状态转移规则和蚂蚁的信息素更新方式,并用模拟退火算法动态的调整参数,有效地帮助算法跳出局部最优解.最后通过与文献比较和Solomon算例的测试,验证了该干扰策略和算法的有效性.To solve the problem of actual logistics distribution, the distribution plans are often changed by the customer’s time window, which leads to the impact on the satisfaction of other customers. The theory of cumulative prospect is proposed, the product of value function and probability weight is established to measure customer satisfaction, and the disruption minimization strategy and disruption recovery model are designed by the disruption management method. At the same time, the an improved adaptive ant colony algorithm is proposed, which improves the state transition rules and the ant pheromone update method. In addition, the simulated annealing algorithm is used to adjust dynamically the parameters to help the algorithm jump out of the local optimal solution. Finally, the effectiveness of the proposed interference strategy and algorithm is verified by comparing with literature and Solomon example.

关 键 词：累积前景理论 干扰管理 物流配送 蚁群算法 模拟退火算法 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] F252.1[自动化与计算机技术—控制科学与工程]