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Application of Genetic Algorithm in the Machinery and Tractor Park Selection

机译:遗传算法在机械和拖拉机公园选择中的应用

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Several technological operations, which involved various aggregates, can be perform at the same time in annual cycle of technological operations performance. The space of solutions is a set of variants selection in the task of machinery and tractor park selection. The complexity of the valuation of received variants consists in the large amount of solution set. It is described one of methods of machinery and tractor park selection by imposition of limitations. The task is divided on subtask and the variants with minimal costs of each subtask are sought separately. The sum of minimum costs by each subtask will be equal the minimum of whole task. A genetic algorithm is proposed to reduce solution set. It allows to reduce the number of variants of machinery and tractor park selection in the calculation process and significantly to accelerate the calculations. There are defined the basic concepts of genetic algorithm (phenotype, genotype, individual, chromosome, parent) for the task of machinery and tractor selection. It is given an example of genetic algorithm application to the task of machinery and tractor park selection. The web-complex "PIKAT" is developed on base of the described algorithm for decision-making support and operating control of agricultural enterprises.
机译:涉及各种聚集体的几种技术操作可以在技术运营性能的年度周期中同时进行。解决方案的空间是机械和拖拉机公园选择任务中的一组变体选择。接受变体估值的复杂性包括大量解决方案集。它描述了通过施加限制来选择机械和拖拉机公园选择之一。任务在SubTask上划分,并单独寻找每个子任务的最小成本的变体。每个子任务的最小成本的总和将等于整个任务的最小值。提出了一种遗传算法来减少解决方案集。它允许减少计算过程中机器和拖拉机停放选择的变体的数量,并显着加速计算。确定机械和拖拉机选择的任务的遗传算法(表型,基因型,个体,染色体,父母)的基本概念。给出了遗​​传算法应用于机械和拖拉机公园选择的遗传算法应用的一个例子。网络复杂的“PIKAT”是在所描述的算法基础上开发的,用于农业企业的决策支持和操作控制。

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