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Emergency scheduling optimization based on improved artificial bee colony algorithm

机译:基于改进的人工蜂菌落算法的紧急调度优化

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When large scale disaster occurs suddenly, allocating scheme of the first batch of "life" emergency supplies directly determines rescue effect. To make lack loss evaluation of the supplies accordant with actual cases, this paper proposed nonlinear loss evaluation function, based on which constructed multi to multi constrained scheduling model with multi objectives. To improve the performance of artificial bee colony algorithm, this paper proposed following schemes: food sources initialization based on converse food source.; reverse learning and comprehensive learning added into bee searching procedure. Experiments results on random data of three scales show that non dominated front solutions set solved by the improved algorithm is more diverse, wide spread and uniform.
机译:当突然发生大规模灾害时,第一批“生命”应急供应的分配方案直接确定救援效果。本文提出了缺乏对实际情况的损失评估,提出了非线性损耗评估功能,基于多于多目标的多约束调度模型。为了提高人造蜂菌落算法的性能,本文提出了以下方案:基于逆转食物来源的食物来源初始化。蜜蜂搜索程序中添加了反向学习和综合学习。实验结果三个尺度的随机数据显示,通过改进的算法解决的非主导的前解决方案更多样化,广泛的扩散和均匀。

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