Abstract
This work aimed to apply genetic algorithms (GA) and particle swarm optimization (PSO) in cash balance management using Miller-Orr model, which consists in a stochastic model that does not define a single ideal point for cash balance, but an oscillation range between a lower bound, an ideal balance and an upper bound. Thus, this paper proposes the application of GA and PSO to minimize the Total Cost of cash maintenance, obtaining the parameter of the lower bound of the Miller-Orr model, using for this the assumptions presented in literature. Computational experiments were applied in the development and validation of the models. The results indicated that both the GA and PSO are applicable in determining the cash level from the lower limit, with best results of PSO model, which had not yet been applied in this type of problem.
Highlights
Manage the available cash balance is a constant problem in all organizations
The results showed that the two algorithms can determine the parameter lower bound (LB) relative to LB*, with a mean standard deviation (MSD) between the Total Cost of genetic algorithms (GA) and particle swarm optimization (PSO) of 0.21%
The PSO model had better results than the GA model in all problems, but the difference between the results of GA in relation to the Control Algorithm is only 0.21%, indicating the GA is fit for use in this type of problem
Summary
Manage the available cash balance is a constant problem in all organizations. This due to the daily inand outflows of cash, whether by the activities of the company or financial transactions that it had negotiated. There is need to control financial resources to obtain the best result for the organization. In this way, the function of cash management has responsibilities such as mobilize, control and plan the financial resources of the companies (SRINIVASAN; KIM, 1986). The use of models to support the decision-making with the application of metaheuristics becomes pertinent, since they can provide a comprehensive and optimization view of something that hardly can be obtained without using methodologies (VOβ, 2001)
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