Considering the uncertainty of logistics demand network, the interval number was used to measure uncertain variables and parameters. The bilevel programming model of logistics network under interval demand mode was established and a hierarchical interval optimization genetic algorithm with interval variables and parameters was designed. The risk coefficient and the maximum decision-making deviation were defined to solve the problem, and the rules for logistics network structure were given to transform the model with certainty. The initial population was defined by interval slack variables and 0- 1 decision variable, with two-stage genetic operation to solve interval optimal solution and node decision-making scheme of bilevel programming objects under different scenarios. The results of tested example show that the operability of the algorithm is much stronger and the solution result has superiority in interval optimal solution and scenario decision.%考虑物流网络需求的不确定性,利用区间参数度量不确定性变量与参数,建立区间需求模式下的物流网络双层规划模型,设计了一种含区间参数与变量的递阶优化遗传算法,通过定义问题求解的风险系数与最大决策偏差,给出适合物流网络结构的区间运算准则,实现模型的确定性转化.以区间松弛变量与0-1决策变量定义初始种群,通过两阶遗传操作运算,求解不同情景下双层规划目标的区间最优解与节点决策方案.算例测试表明算法求解的可操作性更强,求解结果具有区间最优解与情景决策的优越性.
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