摘要
针对战时情况下多机种综合保障基地作战飞机分散式加油车辆调度优化的实际问题,基于设备设施能力的约束,以最小化加油车最大完工时间为目标函数,建立了符合实际情况的数学模型。在问题求解方面,将量子行为引入基本PSO算法,构建出一种性能更好的QDPSO算法。实验表明,该算法能弥补基本PSO算法易陷入局部最优和早熟收敛的不足,在全局和局部解空间搜索效率和质量上表现更优,能够很好地解决所研究的问题。
To solve the vehicle scheduling problem of dispersive refueling for warplanes in the comprehensive multi-type warplanes support base during wartime, we collected relative data and clarified the relationship among the them. Then we established the mathematical model of the problem to minimize the refueling vehicles＇ maximum completion time which was the objective function of the model under the constraint of the capacity of the vehicles and facilities. To solve the problem, we combined the quantum behavior with the PSO algorithm and formulated the quantum-behaved dispersive PSO algorithm. This algorithm solved the problem of local optimization and premature convergence.
出处
《物流技术》
北大核心
2013年第4期265-268,共4页
Logistics Technology
基金
国家社科基金与后期资助项目(10GJ238-44
12FJS004)
后勤工程学院创新基金项目(06YZ42501)
重庆市教委项目(KJZH10218)
关键词
多机种作战飞机
加油车
调度优化
量子行为
粒子群算法
multi-type combat airplane
refueling vehicle
scheduling optimization
quantum behavior
PSO
