Multiobjective Optimization Approach: Thermal Food Processing

The objective of this study was to utilize a multiobjective optimization technique for the thermal sterilization of packaged foods. The multiobjective optimization approach used in this study is based on the optimization of well-known aggregating functions by an adaptive random search algorithm. The...

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Bibliographic Details
Published in:Journal of food science Vol. 74; no. 9; pp. E471 - E487
Main Authors: Abakarov, A, Sushkov, Y, Almonacid, S, Simpson, R
Format: Journal Article
Language:English
Published: Malden, USA Blackwell Publishing Inc 01.11.2009
Wiley
Wiley Subscription Services, Inc
Subjects:
aggregating functions
Algorithms
analysis
Animals
Chemical Phenomena
Computer Simulation
Food Handling
Food Handling - methods
Food Microbiology
Food Packaging
Food Parasitology
food processing
Food processing industry
food processing quality
Food science
Food Technology
Food Technology - methods
Geobacillus stearothermophilus
Geobacillus stearothermophilus - growth & development
growth & development
heat treatment
Hot Temperature
literature reviews
Meat Products
Meat Products - analysis
Meat Products - microbiology
methods
Microbial Viability
microbiology
Models, Biological
multiobjective optimization
multiobjective optimization technique
Numerical Analysis, Computer-Assisted
Optimization algorithms
Optimization techniques
Quality Control
Sterilization
Sterilization - methods
sterilizing
Sus scrofa
Sus scrofa - microbiology
thermal processing of packaged foods
Thiamine
Thiamine - analysis
Time Factors
ISSN:0022-1147, 1750-3841, 1750-3841
Online Access:Get full text
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Summary:The objective of this study was to utilize a multiobjective optimization technique for the thermal sterilization of packaged foods. The multiobjective optimization approach used in this study is based on the optimization of well-known aggregating functions by an adaptive random search algorithm. The applicability of the proposed approach was illustrated by solving widely used multiobjective test problems taken from the literature. The numerical results obtained for the multiobjective test problems and for the thermal processing problem show that the proposed approach can be effectively used for solving multiobjective optimization problems arising in the food engineering field.
Bibliography:http://dx.doi.org/10.1111/j.1750-3841.2009.01348.x
ArticleID:JFDS1348
istex:B42C915DEAB53AB453535E87588F38819F7BA86C
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ObjectType-Feature-1
content type line 14
ObjectType-Article-1
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ISSN:0022-1147
1750-3841
1750-3841
DOI:10.1111/j.1750-3841.2009.01348.x