Search Results (2)

Construction contractors often rely on external funding to manage financial deficits caused by irregular cash inflows and outflows. To address these cash flow challenges, contractors typically adjust the start times of project activities to prevent shortages while minimizing the overall project duration. However, in severe cases, operations may need to halt if cash flow issues cannot be adequately resolved. This study introduces an alternative strategy to prevent cash shortages by allowing for the temporary suspension of activities, known as activity splitting. In this approach, operations are paused to conserve cash and then resumed when sufficient funds become available. The potential benefit of this method is illustrated through a simple, four-activity project. Extending the application to more complex projects with a set of splittable activities—each having different cash requirements, durations, and associated splitting costs—the challenge lies in identifying the optimal activities to split and determining the precise suspension and resumption times, all while minimizing or avoiding project delays and additional costs. To address this, we present a novel mixed-integer linear programming (MILP) model that optimizes the scheduling and splitting of activities to minimize project duration without breaching financial constraints. The MILP model effectively identifies the best trade-off between activity splitting and project extension, taking into account the financial and cost implications of the contractor’s constraints. This is demonstrated through a case study that considers different scenarios related to splitting costs and financial limitations. Full article

This paper develops a Mamdani fuzzy logic system (FLS) that has stochastic fuzzy input variables designed to identify cash-flow deficits in bank lending policies. These deficits do not cover the available cash-flow (CFA) resulting from the company’s operating activity. Thus, due to these deficits, solutions must be identified to avoid companies’ financial difficulties. The novelty of this paper lies in its using stochastic fuzzy variables, or those categories of variables that are defined by fuzzy sets, characterized by normally distributed density functions specific to random variables, and characterized by fuzzy membership functions. The variation intervals of the stochastic fuzzy variables allow identification of the probabilistic risk situations to which the company is exposed during the crediting period using the Mamdani-type fuzzy logic system. The mechanism of implementing the fuzzy logic system is based on two stages. The first is based on the determination of the cash-flow requirements resulting from loan reimbursement and interest rates. This stage has the role of determining the need for financial resources to cover the liabilities. The second stage is based on the identification of the stochastic fuzzy variables which have a role in influencing the cash flow deficits and the probability values estimation of these variables taking into account probability calculations. Based on these probabilistic values, using the Mamdani fuzzy logic system, estimations are computed for the available cash-flow (the output variable). The estimated values for CFA are then used to detect probability risk situations in which the company will not have enough resources to cover its liabilities to financial creditors. All the FLS calculations refer to future time periods. Testing and simulating the fuzzy controller confirms its functionality. Full article