Cost Operation Optimization with Binary Integer Linear Programming in a Cosmetic Company

Small- and medium-sized enterprises (SMEs) represent 70% of employment and contribute to 25% of the GDP in Ecuador’s economy. Since SMEs depend heavily on efficiently managing their economic resources to maintain competitiveness and sustainability, optimizing operational costs, including raw materials and packaging materials, is crucial. This chapter proposes an integer linear programming model to minimize operating costs by selecting the best supplier for each material. The model was solved using the lpsolve package of the free programming language R and the supplier information available in the database of an Ecuadorian cosmeceutical company. The results indicate that the Binary Integer Linear Programming (BILP) model allows selecting a single supplier for each raw material and packaging, fulfilling the objective function and imposed constraints. Compared to empirical supplier selection, the optimization model reduced the company’s total purchasing cost by 13% for the company. Although the model was designed for a typical SME, it can be modified to allow for the selection of multiple suppliers at once, which is particularly useful in cases of material scarcity. The mathematical model represents an efficient and systematic tool for supplier selection and decision-making, reducing uncertainty, time, and human resources required for this task.