MULTI-OBJECTIVE OPTIMIZATION OF DEEP-FAT FRYING OF OSTRICH MEAT PLATES USING MULTI-OBJECTIVE PARTICLE SWARM OPTIMIZATION (MOPSO)

Deep-fat frying (DFF) is a very old process that has grown exponentially over the last years. The attainment to a high and constant quality of fried products with appropriate oil content is of considerable interest to food industry and consumers; however, the theoretical aspects of the frying process are highly complex and difficult to understand. Many efforts were done in order to optimize and control the frying process. The majority of the authors have considered the use of single-objective for the optimization. However, the simultaneous optimization of several objectives is much more realistic and desirable. In this study a multi-objective optimization for DFF of ostrich meat plates was performed. Multi-objective particle swarm optimization is used to obtain the best solutions. This problem has three objective functions that must be satisfied simultaneously. Results show a Pareto that all the points on this Pareto are the best possible solutions.