Cash management policies by evolutionary models: a comparison using the Miller-Orr model

Authors

  • Marcelo Botelho da Costa Moraes University of Sao Paulo, Sao Carlos, SP, Brazil
  • Marcelo Seido Nagano

DOI:

https://doi.org/10.4301/S1807-17752013000300006

Abstract

This work aims to apply genetic algorithms (GA) and particle swarm optimization (PSO) to managing cash balance, comparing performance results between computational models and the Miller-Orr model. Thus, the paper proposes the application of computational evolutionary models to minimize the total cost of cash balance maintenance, obtaining the parameters for a cash management policy, using assumptions presented in the literature, considering the cost of maintenance and opportunity for cost of cash. For such, we developed computational experiments from cash flows simulated to implement the algorithms. For a control purpose, an algorithm has been developed that uses the Miller-Orr model defining the lower bound parameter, which is not obtained by the original model. The results indicate that evolutionary algorithms present better results than the Miller-Orr model, with prevalence for PSO algorithm in results.

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Published

2013-09-01

Issue

Section

Artigo Original

How to Cite

Cash management policies by evolutionary models: a comparison using the Miller-Orr model . (2013). Journal of Information Systems and Technology Management, 10(3), 561-576. https://doi.org/10.4301/S1807-17752013000300006