Abstract:

To identify the impact of uncertain risk on the integration of logistics resources, this paper develops a bilevel programming model from the perspective of the entire port supply chain which considers the logistics service requester, logistics service provider and port enterprises. The upper model optimizes the integration strategy of multiple ports on the chain to the upstream and downstream enterprises under the given confidence level of the decision maker and the risk of node interruption and demand uncertainty. The lower model optimizes the integration strategy from the port supply chain enterprise nodes and aims to minimize the total cost of transportation and achieve an equilibrium flow of goods. The hybrid genetic algorithm is designed to solve the model. The study results show that, in the risk situations, the logistics service provider would have more benefits if they participate in the port integration than not participate. The different confidence levels of the decision makers on the two risk situations would affect the integration strategies of each port on the chain, and the risk of node interruption has more impact on the benefit of the port supply chain.

Key words: transportation economy, resource integration, hybrid genetic algorithm, port supply chain, uncertainty

摘要：

为探索不确定风险对物流资源整合的影响，以整个港口供应链为视角，综合考虑物流服务需求方、物流服务供应商、港口企业，构建不确定双层规划模型。上层模型从港口供应链整体角度出发，以整合收益最大化为目标，在给定决策者对于节点中断和需求不确定风险的置信水平下，优化链上多港口对上下游企业的整合策略；下层模型从港口供应链企业节点角度出发，以运输需求方总成本最小为目标，优化整合策略下的均衡货流量。设计混合遗传算法求解案例。案例结果表明：在遭遇风险的情况下，物流服务供应商参与港口整合相较于不参加，链条整体可以获得收益更大；依据决策者对于两种风险置信水平的不同，链上各个港口的整合策略将呈现明显的差异性，且节点中断风险对港口供应链收益情况的影响更大。

关键词: 交通经济, 资源整合, 混合遗传算法, 港口供应链, 不确定性