不确定条件下后装协同保障链优化调度

后装保障链是联合作战环境下的重要支撑, 针对保障链中的2个重要节点-前进基地和保障基地的资源协调问题, 提出了考虑不确定因素影响的优化模型及基于信息共享的协同保障算法; 为了解决保障数据样本较小情况下的不确定参数估算问题, 利用模糊规划方法把不确定优化模型转化为概率约束模型; 并利用增强ε-约束法来估算多目标Pareto解, 帮助后装指挥人员在难以事先给出权重的情况下选择合适的解决方案; 为了解决规划模型的计算复杂性过大的问题, 设计了嵌入自适应大规模邻域搜索的Memetic算法进行求解。最后通过仿真实验对模型和算法的有效性进行了验证。

Optimal scheduling for cooperative support chain of logistics and equipment under uncertainty

Logistics and equipment support chain is an important support in joint operational environment.In order to solve the resource coordination problem between the two key members of support chain for forward operating base and support base,an optimal model considering the influence of uncertainty factor and its corresponding cooperation support algorithm based on information exchange are proposed.The optimal model under uncertainty is transformed into probabilities constraint model with the fuzzy programming method to solve the problem of uncertain parameter estimation in the case of small data sample problem.Augmentedε-constraint method is adopted to estimate the multi-objective Pareto solutions,which helps the logistics and equipment commander to choice the suitable solution without a priori weight knowledge.Furthermore,a Memetic algorithm with adaptive large neighborhood search heuristic is proposed to face the computation complexity of the programming model.Finally,the simulation experiments show that the models and algorithms are efficient.