Toward innovative smart agroalimentary solutions: A pilot optimization algorithm for selecting Oaxaca cheese with nutritional constraints

Abstract

This work presents a combined analysis of the physicochemical characterisation of traditional and commercial Oaxaca cheeses, together with a pilot combinatorial optimisation study using a multi-objective optimisation algorithm. Cheeses that best meet nutritional content standards and regulatory restrictions were selected. Six samples were analysed for nutritional composition, including moisture, protein, and fat, using methods established by the Association of Official Analytical Chemists (AOAC). The field data were used to formulate a linear programming model with constraints derived from current regulations (COFOCALEC 733-2013), which concurrently maximises protein and fat content while minimising moisture. The results indicate that traditional cheeses contain average protein and fat contents of 21.7% and 25.4%, respectively, exceeding those of commercial cheeses (17.14% and 21.2%). The proposed algorithm was tested in a real case study, where it selected traditional cheeses on the basis of their higher nutritional value, as defined by the objective function. This optimal cheese selection methodology could be applied to problems involving extensive databases (Big Data) to support the definition of physicochemical characteristics relevant to the quality assessment of Oaxaca cheeses. Smart citations: https://scite.ai/reports/10.61467/2007.1558.2026.v17i1.1182Dimensions.Open Alex.