Strategies to reduce costs in the planning of house building projects with government financing for low-income populations

Abstract

The execution of housing construction projects for low-income populations in developing countries requires projects with low diversification, using quality materials and meeting project deadlines, qualified workforce are essential actions for the success of these projects. Thus, this work aims to simulate aggregate planning strategies in housing construction projects for low-income populations financed by the government. The methodology consisted of the simulation of four aggregate planning strategies (demand monitoring, constant workforce allowing for delays, constant workforce without delays and mixed) using the entire linear programming technique. The methodology used was a two-year case study in twelve civil construction projects for a civil construction company whose market segment is low-income housing with public funding. The chosen strategy with the lowest cost was the mixed strategy, which presented the lowest cost, with hiring employees and no layoffs. The aggregate planning simulation also did not show delays in the 12 projects, proving to be an efficient alternative for the planning management of companies that operate several projects at the same time.