A Decision Tool based on a Multi-Objective Methodology for designing High-Pressure Thermal Treatments in Food Industry Miriam R. Ferr´ andez a,1 , Juana L. Redondo a , Benjamin Ivorra b , ´ Angel M. Ramos b , Pilar M. Ortigosa a a Dept. de Inform´ atica, Universidad de Almer´ ıa, ceiA3, Ctra. Sacramento, La Ca˜ nada de San Urbano, 04120 Almer´ ıa, Spain b Instituto de Matem´ atica Interdisciplinar (IMI) & Dept. de Matem´atica Aplicada, Universidad Complutense de Madrid, Plaza de las Ciencias, 3, 28040 Madrid, Spain Abstract In this work, we propose a methodology for designing High-Pressure Ther- mal processes for food treatment. This approach is based on a multi-objective preference-based evolutionary optimization algorithm, called WASF-GA, com- bined with a decision strategy which provides the food engineer with the best treatment in accordance with some quality requirements. The resulting method is compared to a mono-objective optimization algorithm called MLS-GA. To do so, we consider several particular mono-objective and multi-objective optimiza- tion problems. Then, considering those cases, we determine an adequate set of parameters for the WASF-GA and the MLS-GA algorithms in order to obtain a reasonable compromise between solution quality and computational time. Next, we compare the results obtained by the WASF-GA and MLS-GA. Additionally, the best solutions returned by the WASF-GA are analyzed from a food engi- neering point of view. Finally, a sensitivity analysis regarding the impact of design parameters on the performances of those solutions is performed. Keywords: Decision Support System, Genetic algorithms, Metaheuristics, Food Industry, High-Pressure 1. Introduction High-Pressure (HP) technology is widely used in food treatment processes [1]. In the last decades, its popularity has grown significantly due to the in- creasing demand for healthy and safe products, minimally processed, and at the Email addresses: mrferrandez@ual.es (MiriamR.Ferr´andez), jlredondo@ual.es (Juana L. Redondo), ivorra@mat.ucm.es (Benjamin Ivorra), angel@mat.ucm.es ( ´ Angel M. Ramos), ortigosa@ual.es (Pilar M. Ortigosa) 1 Corresponding author. Preprint submitted to Optimization Online February 1, 2018