模糊资源约束的飞机消耗件联合补充研究

针对不确定环境下飞机消耗件联合补充的问题，建立模糊资源约束的消耗件联合补充模型。以最小化费用为目标，运用模糊数学规划，将模糊约束模型转换为确定约束模型。为提高模型的求解速度和效果，提出综合考虑种群特征、个体特征和种群进化阶段特征的改进自适应遗传算法，并通过仿真实例，对比分析模糊约束模型和确定约束模型的结果，以及一般遗传算法和改进自适应遗传算法的性能。结果表明：改进自适应遗传算法能保持种群多样性，具有良好的收敛性，算法搜索速度快，寻优能力强，其求解的精度和速度均优于一般遗传算法。

Research on Joint Replenishment Problem of Aircraft Consumable Items with Fuzzy Resource Constraint

To deal with the aircraft consumable items joint replenishment problem with fuzzy resource constraint, the consumable items joint replenishment model with fuzzy resource constraint was constructed. To minimize the cost as the target, the fuzzy constraint model was converted to deterministic constraint model by using of fuzzy mathematical programming. In order to improve the rate and effect of resolving the model, the improved adaptive genetic algorithm which took into account the population characteristics, the individual characteristics, and the population evolution characteristics, was proposed. Through simulation examples, the comparisons between the fuzzy constraint model and deterministic constraint model were made, and also the general genetic algorithm and the improved adaptive genetic algorithm. The results showed that the improved adaptive genetic algorithm could keep the population diversity and had good convergence. The algorithm had fast search and optimization capability, and its precision and speed of solving were superior to general genetic algorithm.