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Otimiza??o do saldo de caixa com algoritmos genéticos: um estudo relacionando cruzamento e muta??o no modelo de Miller e Orr

机译:使用遗传算法优化现金余额:关于Miller和Orr模型中的交叉和突变的研究

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This work has the objective to apply genetic algorithms in cash balance policy definition. This financial problem was initially treated by Baumol (1952) and Tobin (1956) which work applies deterministic models to inventory control in enterprises cash balance. Further, Miller and Orr (1966) enhanced the problem approach introducing a stochastic model which no longer defines the optimal cash balance, but bands of oscillation. This work proposes an evolutionary model methodology with genetic algorithms, in different approaches to cash balance optimization, using the premises showed in literature. For this, simulations are used in model support and validation. The results shows that genetic algorithms can be very useful in Miller-Orr model parameterization, with good results in this field of problem, and the optimal solution has a strong association with mutation evolutionary process. This paper let future perspectives of better application of genetic algorithms in cash balance optimization problem.
机译:这项工作的目的是在现金余额政策定义中应用遗传算法。这个财务问题最初由Baumol(1952)和Tobin(1956)处理,他们将确定性模型应用于企业现金余额中的库存控制。此外,Miller和Orr(1966)改进了问题方法,引入了一种随机模型,该模型不再定义最佳现金余额,而是波动范围。这项工作提出了一种遗传模型的进化模型方法,并采用文献中显示的前提,采用了不同的现金余额优化方法。为此,在模型支持和验证中使用了仿真。结果表明,遗传算法在Miller-Orr模型参数化中非常有用,在该问题领域取得了良好的效果,最优解与突变进化过程密切相关。本文提出了遗传算法在现金余额优化问题中更好地应用的未来观点。

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