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A Genetic Algorithm applied to pick sequencing for billing

机译：一种遗传算法应用于挑选计费测序

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This article addresses the use of Holland's Genetic Algorithms (GAs) (Holland in Adaptation in natural and artificial systems, University of Michigan Press, Ann Arbor, MI, 1975) in solving an optimization problem not exploited yet by literature, which we have named Optimal Billing Sequencing (OBS). The objective of the GA proposed is to automate pick sequencing, which addresses the process of allocating the stock available for sale to the purchase orders in a portfolio, so that the maximization of the billing is the optimal result for the OBS. A modelling and computational simulation methodology has been employed. Such methodology is designed to enable the GA to meet the boundary conditions established by predefined decision restrictions and parameters. We have reached the conclusion, by means of experimental tests, that the GA developed satisfactorily solves the problem studied. In addition to a low computational overhead, the GA reduces operating costs and speeds picking decision-making processes and billing processes.
机译：本文涉及荷兰遗传算法（天然气）（荷兰在自然和人工系统中，密歇根大学的荷兰，Ann Arbor，Mi，1975）在解决未被文学中汲取的优化问题，我们已评为最优计费测序（OBS）。 GA提出的目的是自动化挑选排序，该挑选是将可用于向投资组合中的采购订单分配销售的股票的过程，以便计费的最大化是OBS的最佳结果。采用了建模和计算模拟方法。这种方法旨在使GA能够满足由预定义决策限制和参数建立的边界条件。我们通过实验测试得出了得出的结论，即GA开发的令人满意地解决了所研究的问题。除了低计算开销之外，GA还降低了运营成本和速度采摘决策过程和计费过程。

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