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One improved genetic algorithm applied in the problem of dynamic jamming resource scheduling with multi-objective and multi-constraint

机译:一种改进的遗传算法在多目标多约束动态干扰资源调度中的应用

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In this paper we proposed a mathematical model for mission planning problem of collaborate jamming resource. In the practical problem of collaborate jam of warships and aircrafts computational time is limited stiffly, and the allocation scheme of multiple targets and multiple jamming devices should be dynamical in practical case. Moreover, the problem is multi-objective and multi-constraint conditions in nature. To resolve the inefficient of algorithms in existing papers we present a improved algorithm With Repair Process based on GA(WRPGA) to address the problems of scheduling of dynamic jamming resource with multi-objective and multi-constraint conditions. Computational results of our experiments have shown that the WRPGA with highly efficiency performance, the quality of optimize solution of WRPGA is better than IIGA which we present in early paper[5] within moderate or acceptable computational time, the WRPGA can obtain dynamical allocation scheme in acceptable computational time for the problem of scheduling of jamming resource, our algorithm can be widely applied to the general mission planning problems needn't modify the algorithm.
机译:在本文中,我们为协作干扰资源的任务计划问题提出了一个数学模型。在军舰与飞机协同干扰的实际问题中,计算时间受到严格限制,在实际情况下,多目标多干扰设备的分配方案应该是动态的。而且,问题本质上是多目标和多约束条件。为了解决现有论文中算法的低效率问题,我们提出了一种基于GA的改进的带修复过程的算法(WRPGA),以解决多目标多约束条件下动态干扰资源的调度问题。实验的计算结果表明,WRPGA具有较高的效率,在适当的或可接受的计算时间内,WRPGA的优化解决方案的质量要优于我们在早期论文[5]中提出的IIGA,WRPGA可以得到动态分配方案。对于干扰资源调度问题而言,在可接受的计算时间上,我们的算法可以广泛应用于不需要修改算法的一般任务计划问题。

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