The tactical management of cash flow is critical in financial management of a company or organization. Several mathematical models for planning cash flow have been proposed in recent decades. Most of the models are deterministic and initially treated as an extension of the economic order quantity. This thesis addresses the cash management problem from the perspective of optimization models present in the Operations Research literature. The aim is to study, develop and apply formulations based on mathematical programming and network flows, considering uncertainties in parameters, to support the decisions involved in managing the cash flow. A case study was developed in a typical company of the stationery sector to analyze the suitability and potential of the proposed approaches for companies of this sector. For that, this thesis implement robust optimization and stochastic programming to address the parameters uncertainties in the problem of maximizing the available financial resources at the end of a multi-period and finite planning horizon of the company's cash flow. The proposed approaches are based on a deterministic model which uses a network flow to maximize the cash flow return at the end of the period. For the treatment of uncertainties in the parameters that define the flow of financial resources in time are used the robust optimization approach of worst case interval and the stochastic programming approach risk neutral, minimax with regret and conditional value-at-risk. There were no other studies in the literature following this line of research. As shown in this thesis the proposed approaches can generated promising results for the management of cash flow in companies of the stationery sector and others, with significant contributions in financial decision-making department, particularly for the treatment of uncertainties in the parameters of the cash flow.
|Publication status||Unpublished - 2015|