Food processing optimization using evolutionary algorithms

Abstract

Evolutionary algorithms are widely used in single and multi-objective optimization. They are easy to use and provide solution(s) in one simulation run. They are used in food processing industries for decision making. Food processing presents constrained and unconstrained optimization problems. This paper reviews the development of evolutionary algorithm techniques as used in the food processing industries. Some evolutionary algorithms like genetic algorithm, differential evolution, artificial neural networks and fuzzy logic were studied with reference to their applications in food processing. Several processes involved in food processing which include thermal processing, food quality, process design, drying, fermentation and hydrogenation processes are discussed with reference to evolutionary optimization techniques. We compared the performances of different types of evolutionary algorithm techniques and suggested further areas of application of the techniques in food processing optimization.

Key words: Evolutionary algorithms, optimization, food processing, multi-objective, constrained and unconstrained.