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Solving the Problem of Distribution of Fiscal Coupons by Using a Steady State Genetic Algorithm

机译:用稳态遗传算法解决财政优惠券分布问题

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摘要

When customers buy goods or services from business entities they are usually given a receipt that is known with the name fiscal or tax coupon, which, among the others, contains details about the value of the transaction. In some countries, the fiscal coupons can be collected during a certain period of time and, at the end of the collection period, they can be handed over to the tax authorities in exchange for a reward, whose price depends on the number of collected coupons and the sum of their values. From the optimisation perspective, this incentive becomes interesting when, both the number of coupons and the sum of their value is large. Hence, in this paper, we model this problem in mathematical terms and devise a test set that can be used for benchmarking purposes. Furthermore, we propose a solution based on Genetic Algorithms, where we compare its results versus the results to the solution of the relaxed versions of the proposed problem. The computational experiments indicate that the proposed solution obtains promising results for complex problem instances, which show that the proposed algorithm can be used to solve realistic problems in a matter of few seconds by utilizing standard personal computers.
机译:当客户从商业实体购买商品或服务时,他们通常会收到一份收据,这些收据是名称或税收优惠券,其中包括其他有关交易价值的详细信息。在一些国家,可以在一段时间内收集财政优惠券,并且在收集期结束时,他们可以被移交给税务机关以换取奖励,其价格取决于所收集的优惠券的数量和他们的价值的总和。从优化角度来看,当优惠券的数量和它们的价值总和都是大的,这种激励变得很大。因此,在本文中,我们在数学术语中模拟了这个问题,并设计了可用于基准测试的测试集。此外,我们提出了一种基于遗传算法的解决方案,在那里我们将其结果与结果与所提出的问题的放宽版本的解决方案进行比较。计算实验表明,所提出的解决方案获得了复杂问题实例的有希望的结果,这表明所提出的算法可以通过利用标准的个人计算机来解决几秒钟的现实问题。

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