Single- and Multi-Objective Optimization of Low Fat Ice-Cream Formulation, Based on Genetic Algorithms

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Application of either protein or carbohydrate-based products as fat replacers in low fat ice-creams can improve the properties of these products. However, the type and level of fat and fat replacer utilized are affected by such different parameters as functional ones, namely: viscosity and overrun, hardness and melting rate, nutritional properties (calories) as well as the price of the final product. Throughout the present study, single- and multi-objective optimization method as based on the genetic algorithms (GAs) was applied to select the suitable fat-free as well as low-fat ice-cream formulations. The data related to single-objective optimization of selected parameters revealed that the ice-creams containing 3.5% Simplesse plus 1.72% fat, and 2.95% Maltodextrin plus 1.87% fat have ended up with the most desirable functional objectives. The application of multi-objective optimization led to a range of solutions of different fat and fat replacer contents out of which the producers can adopt the most suitable choice depending on the needs.