Applied Soft Computing Journal 79 (2019) 326–340 Contents lists available at ScienceDirect Applied Soft Computing Journal journal homepage: www.elsevier.com/locate/asoc Preference-based multi-objectivization applied to decision support for High-Pressure Thermal processes in food treatment Miriam R. Ferrández a,∗ , Juana L. Redondo a , Benjamin Ivorra b , Ángel M. Ramos b , Pilar M. Ortigosa a a Dept. de Informática, Universidad de Almería, ceiA3, Ctra. Sacramento, La Cañada de San Urbano, 04120 Almería, Spain b Instituto de Matemática Interdisciplinar (IMI) & Dept. de Matemática Aplicada, Universidad Complutense de Madrid, Plaza de las Ciencias, 3, 28040 Madrid, Spain highlights • The problem of finding the best High-Pressure configuration is solved. • The preference-based evolutionary algorithm WASF-GA is used. • A new decision tool for food engineers is proposed and validated. • A comparison between multi-objective and mono-objective solutions is conducted. article info Article history: Received 11 April 2018 Received in revised form 5 February 2019 Accepted 29 March 2019 Available online 8 April 2019 Keywords: Multi-objectivization Decision support system Genetic algorithm Metaheuristic Food industry High-pressure abstract Food industry aims to provide healthy products that must satisfy the quality requirements of the considered legislation. To do so, food is treated by using some processing techniques, such as High- Pressure Thermal (HPT) treatments. In this work, we propose a preference-based multi-objectivization methodology to design HPT processes for food treatment. This approach is based on formulating a multi-objective optimization problem, instead of a constrained mono-objective problem, where the constraints are reformulated as separate objective functions. The multi-objective problem is then solved by using preference-based evolutionary optimization algorithms (PMOEAs). PMOEAs focus the search of a numerical solution inside a region of interest defined by the food engineer, avoiding exploring HPT designs that are out of interest. The proposed methodology is validated by considering several particular mono-objective and multi-objective optimization problems related to HPT processing. In particular, we compare the results obtained by two competitive state-of-the-art PMOEAs, called WASF-GA and R-NSGA-II, with the ones returned by a mono-objective algorithm called MLS-GA. As part of this study, the influence of the optimization algorithm parameters on the solutions, their quality and the computing time are discussed. Finally, the best solutions returned by the algorithm that shows a better performance for our problems, which is WASF-GA, are analyzed from a food engineering point of view and a sensitivity analysis regarding the impact of design parameters on the performances of those solutions is carried out. © 2019 Published by Elsevier B.V. 1. Introduction High-Pressure (HP) technology is widely used in food treat- ment processes [1]. In the last decades, its popularity has grown significantly due to the increasing demand for healthy and safe products, minimally processed, and at the same time, ready for immediate consumption. Among other food treatments, HP ∗ Corresponding author. E-mail addresses: mrferrandez@ual.es (M.R. Ferrández), jlredondo@ual.es (J.L. Redondo), ivorra@mat.ucm.es (B. Ivorra), angel@mat.ucm.es (Á.M. Ramos), ortigosa@ual.es (P.M. Ortigosa). stands out for the two following advantages: it does not use additives that consumers prefer to avoid, and it is not based on extremely high or low temperatures, which can affect nutritional and organoleptic properties of the food. A critical point in the design of food treatments processes (such as HP treatments) is to determine suitable parameters such that the treated product satisfies the desired quality. The quality targets, which are established by the food legislation of each par- ticular country, are frequently expressed in terms of thresholds of unhealthy properties that cannot be overpassed and thresholds of beneficial properties that must be maintained. Then, with the objective of providing food engineers with a decision support https://doi.org/10.1016/j.asoc.2019.03.050 1568-4946/© 2019 Published by Elsevier B.V.