基于马尔科夫链-多目标模型的应急供应链决策优化研究

为应对洪涝、新冠肺炎疫情等突发灾难,提出供应物资满足率最大、供应时间最短、供应成本最低的离散时间马尔科夫链-多目标规划模型(DTMC-MOP),动态地识别、分析、应对应急供应链风险;采用改进自适应NSGA-Ⅱ算法求解优化模型,并通过标准测试函数进行测试与评价,验证模型的可行性和有效性;通过算例分析,获得精度更高、分布更均匀的Pareto最优前沿。研究结果表明:决策者可以依据应急管理核心目标或不同偏好选择相适应的应急方案,研究结果可为应急供应链决策优化提供1种科学方法,对保障灾民生命安全、维护社会和谐稳定具有积极意义。

Research on decision-making optimization of emergency supply chain based on Markov chain and multi-objective model

In order to cope with the sudden disasters such as floods,COVID-19,etc.,a discrete time Markov chain and multi-objective programming model (DTMC-MOP) with the maximum supply satisfaction rate,the shortest supply time and the lowest supply cost was proposed to dynamically identify,analyze and respond to the emergency supply chain risk.The improved self-adaptive Non-dominated Sorting Genetic Algorithm-Ⅱ (NSGA-Ⅱ) was used to solve the optimization model,and the feasibility and effectiveness of the model were verified by testing and evaluation with standard test functions.Through the example analysis,the Pareto optimal front with higher precision and more uniform distribution was obtained.The results showed that the decision-maker could choose the appropriate emergency scheme based on the core objective of emergency management or different preferences.It provide a scientific method for the decision-making optimization of emergency supply chain,which has positive significance for ensuring the life safety of victims and maintaining the social harmony and stability.