Efficient and robust multi-objective optimization of food processing: A novel approach with application to thermal sterilization

Abstract

a b s t r a c tThe optimization of thermal processing of foods is a topic which has received great attention during the last decades. The majority of the authors have considered the use of single-objective (criteria) for the optimization. However, the simultaneous optimization of several objectives is much more realistic and desirable, but the associated non-linear programming problems can be very challenging to solve. Here, we describe an efficient and robust multi-criteria optimization method which can be successfully applied to large dynamic systems, like those arising from the modelling of thermal processing of foods. Further, their capabilities for better design and operation of these processes will be highlighted with selected case studies, where the generated Pareto solutions will be analysed. Finally, we will also illustrate their advantages over other recently proposed strategies.

Study of the impact of a new hurdle technology composed of electro‐activated solution and low heat treatment on the canned pea and corn quality and microbial safety

“…New method requires process optimisation so as to find the optimal balance between heating temperature and the process time in order to maximise the final nutrient retention and assure sufficient microbiological lethality. Furthermore, maximisation of energy efficiency and minimisation of total process time should also be taken into account (Send ın et al, 2010).…”

A new method to obtain fuzzy Pareto set of fuzzy multi-criteria optimization problems

“…Out of them, NBI method [6] has a clear geometric idea and simple to use. Due to that, in the last decade, NBI method has been used extensively [1,14,19,21,22,24,31,34,37,43]. However, NBI has several drawbacks.…”

Multi-Objective Optimization of the Pasteurization Process of Pumpkin Cubes Packaged in Glass Jars

“…However, most optimization studies reported in food engineering refer to singleobjective optimization. Only a few researchers proposed multi-response strategies in the analysis of different food processes: bulk-grain handling [11]; thermal processing [12][13][14][15][16][17]; conventional drying [18][19][20]; osmotic dehydration [10,[21][22][23][24][25][26][27][28]; baking [29][30][31][32][33]; roasting [34,35]. Pasteurization process requires optimization with the purpose of simultaneously diminish costs and undesired effects on the quality in the resulting product.…”