International Journal of Food Studies
Sign in
Issue image

More articles from Volume 2, Issue 1, 2013

Antioxidants, their properties, uses in food products and their legal implications

The impact of cold chain temperature abuses on the quality of frozen strawberries (Fragaria ×ananassa)

A multi-criteria optimization and decision-making approach for improvement of food engineering processes

Effect of antioxidant and optimal antimicrobial mixtures of carvacrol, grape seed extract and chitosan on different spoilage microorganisms and their application as coatings on different food matrices

Effect of Biopreservatives on Storage Life of Papaya (Carica papaya L.)

Citations

Crossref Logo

11

Crossref Logo

A Stolyanov, A Zhuk, A Vlasov, A Maslov, L Kuranova, A Kaychenov

(2019)

Complex for modeling and optimization the sterilization process

IOP Conference Series: Earth and Environmental Science, 403(1)

10.1088/1755-1315/403/1/012016
Crossref Logo

Fatemeh Gholi Zadeh Kharrat, Newton Shydeo Brandão Miyoshi, Juliana Cobre, João Mazzoncini De Azevedo-Marques, Paulo Mazzoncini de Azevedo-Marques, Alexandre Cláudio Botazzo Delbem, Zezhi Li

(2020)

Feature sensitivity criterion-based sampling strategy from the Optimization based on Phylogram Analysis (Fs-OPA) and Cox regression applied to mental disorder datasets

PLOS ONE, 15(7)

10.1371/journal.pone.0235147
Crossref Logo

Alejandro R. Lespinard, Javier R. Arballo, Francisco J. Taus, Rodolfo H. Mascheroni

(2015)

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

International Journal of Food Engineering, 11(5)

10.1515/ijfe-2014-0241
Crossref Logo

Jose Lucas Peñalver-Soto, Alberto Garre, Arantxa Aznar, Pablo S. Fernández, Jose A. Egea

(2021)

Dynamics of Microbial Inactivation and Acrylamide Production in High-Temperature Heat Treatments

Foods, 10(11)

10.3390/foods10112535
Crossref Logo

Daniel Anthony Howard, Bo Nørregaard Jørgensen, Zheng Ma

(2023)

Multi-Method Simulation and Multi-Objective Optimization for Energy-Flexibility-Potential Assessment of Food-Production Process Cooling

Energies, 16(3)

10.3390/en16031514
Crossref Logo

Wendy Fox-Turnbull, Elizabeth Reinsfield

(2022)

Technology across boundaries: preserve or perish

International Journal of Technology and Design Education, 32(5)

10.1007/s10798-021-09700-7
Crossref Logo

Lilly Zeitler, Suwichan Phatthanaphraiwan, Shauna Downs, Bronwen Powell

(2025)

Foraging, Farming or Shopping? A Decision Matrix Approach for Food Environment Assessments

International Journal of Environmental Research and Public Health, 22(5)

10.3390/ijerph22050711
Crossref Logo

Maksims Kazakovs, Anta Verdina, Irina Arhipova

(2015)

Automation of Human Resources Development Planning

Procedia Computer Science, 77()

10.1016/j.procs.2015.12.379
Crossref Logo

Martial Madoumier, Gilles Trystram, Patrick Sébastian, Antoine Collignan

(2019)

Towards a holistic approach for multi-objective optimization of food processes: A critical review

Trends in Food Science & Technology, 86()

10.1016/j.tifs.2019.02.002
Crossref Logo

Masato Sasaki, Anas Laamrani, Mitsuo Yamashiro

(2018)

An interactive genetic algorithm for portfolio optimization considering the decision maker’s preference

Journal of Information and Optimization Sciences, 39(4)

10.1080/02522667.2018.1479208
Crossref Logo

Emadaldin Elfatih M. Abdurrahman, Giovanna Ferrari

(2025)

Digital Twin applications in the food industry: a review

Frontiers in Sustainable Food Systems, 9()

10.3389/fsufs.2025.1538375

A multi-criteria optimization and decision-making approach for improvement of food engineering processes

Alik Abakarov ,
Alik Abakarov
Contact Alik Abakarov

Higher Technical School of Agricultural Engineering, Technical University of Madrid , Madrid , Spain

Institute of canning and vegetable drying industry (VNIIKOP) , Moscow , Russia

View authors publications

Search this author on:

PubMed | Google Scholar
Yuri Sushkov ,
Yuri Sushkov

Mathematics Department, St. Petersburg State University , Saint-Petersburg , Russia

View authors publications

Search this author on:

PubMed | Google Scholar
Rodolfo H. Mascheroni
Rodolfo H. Mascheroni

CIDCA (CONICET - UNLP) and MODIAL Facultad de Ingenierıa Argentina

View authors publications

Search this author on:

PubMed | Google Scholar

Published: 18.04.2013.

Volume 2, Issue 1 (2013)

pp. 1-21;

https://doi.org/10.7455/ijfs.v2i1.79

Abstract

The objective of this study was to propose a multi-criteria optimization and decision-making technique to solve food engineering problems. This technique was demonstrated using experimental data obtained on osmotic dehydration of carrot cubes in a sodium chloride solution. The Aggregating Functions Approach, the Adaptive Random Search Algorithm, and the Penalty Functions Approach were used in this study to compute the initial set of non-dominated or Pareto-optimal solutions. Multiple non-linear regression analysis was performed on a set of experimental data in order to obtain particular multi-objective functions (responses), namely water loss, solute gain, rehydration ratio, three different colour criteria of rehydrated product, and sensory evaluation (organoleptic quality). Two multi-criteria decision-making approaches, the Analytic Hierarchy Process (AHP) and the Tabular Method (TM), were used simultaneously to choose the best alternative among the set of non-dominated solutions. The multi-criteria optimization and decision-making technique proposed in this study can facilitate the assessment of criteria weights, giving rise to a fairer, more consistent, and adequate final compromised solution or food process. This technique can be useful to food scientists in research and education, as well as to engineers involved in the improvement of a variety of food engineering processes.

Keywords

multi-objective optimization,

multi-criteria decision-making,

osmotic dehydration,

adaptive random search,

aggregating functions,

sophisticated software

References

1.
Statnikov R, Matusov J. Multicriteria Optimization and Engineering. 1995;
2.
Keeney R, Raiffa H. Decisions with Multiple Objectives, Preferences and Value Trade Offs. 1993;
3.
Kiranoudis C, Markatos N. Pareto design of conveyor-belt dryers. Journal of Food Engineering. 2000;(3):145–55.
4.
Marler R, Arora J. Survey of multiobjective optimization methods for engineering. Structural and Multidisciplinary Optimization. 2004;(6):369–95.
5.
Mehnen J, Trautmann H. Proceedings of the 5th CIRP International Seminar on Intelligent Computation in Manufacturing Engineering (CIRP ICME ’06). CIRP International Seminar on Intelligent Computation in Manufacturing Engineering. 2006;293–8.
6.
Miller G. The Magical Number 7, Plus or Minus 2 -Some Limits on our Capacity for Processing Information. Psychological Review. 1956;(2):81–97.
7.
Noshad M, Mohebbi M, Shahidi F, Mortazavi S. Multi-Objective Optimization of Osmotic-Ultrasonic Pretreatments and Hot-Air Drying of Quince Using Response Surface Methodology. Food Bioprocess Technology. 2012;(6):2098–110.
8.
Purshouse R, Fleming P, Fonseca C, Fleming, Zitzler E, Deb, et al. LECTURE NOTES IN COMPUTER SCIENCE. 2nd International Conference on Evolutionary Multi-Criterion Optimization. Proceedings. 2003;16–30.
9.
Saaty T. Efficient and robust multiobjective optimization of food processing: A novel approach with application to thermal sterilization. European Journal of Operational Research. 1990;(1):317–24.
10.
Seng C, Rangaiah G. Optimization in Food Engineering. 2008;153–78.
11.
Sharma S, Rangaiah G, Cheah K. Food and Bioproducts Processing. 2012;(C2):123–34.
12.
Siinivas N, Deb K. Multiobjective Optimization Using Nondominated Sorting in Genetic Algorithms. Evolutionary Computation. 1994;(3):221–48.
13.
Singh B, Paramjit S, Nanda V, Bera M. Optimization of Osmotic Dehydration Process of Carrot Cubes in Sodium Chloride Solution. International Journal of Food Engineering. 2008;(2).
14.
Joshua D, David D. Approximating the Nondominated Front Using the Pareto Archived Evolution Strategy. Evolutionary Computation. 2000;(2):149–72.
15.
Statnikov R, Bordetsky A, Statnikov A. Multicriteria analysis of real-life engineering optimization problems: statement and solution. Nonlinear Analysistheory Methods & Applications. 2005;(5–7):685-E696.
16.
Steuer R. Multiple criteria optimization: theory, computation and application. 1985;
17.
Sushkov Y. Multi-objective optimization of multi-regime systems. Digital System Architecture. 1984;21–4.
18.
Tan K, Khor E, Lee T. Multiobjective evolutionary algorithms and applications. Advanced Information and Knowledge Processing. 2005;
19.
Thakur M, Wang L, Hurburgh C. A multi-objective optimization approach to balancing cost and traceability in bulk grain handling. Journal of Food Engineering. 2010;(2):193–200.
20.
Treitz M, Schollenberger I, Schrader B, Geldermann J, Rentz O. RadTech Europe 2005, Conference Proceeding. 2005;155–60.
21.
Vansnick J. On the Problem of Weights in Multiple Criteria Decision-Making (the Noncompensatory Approach). European Journal of Operational Research. 1986;(2):288–94.
22.
Vassilev V, Genova K, Vassileva M. A Brief Survey of Multicriteria Decision Making Methods and Software Systems. Cybernetics and Information Technologies. 2005;(1):3–14.
23.
Winterfeldt V, Edwards D, W. Decision Analysis and Behavioral Research. 1986;
24.
Xu S, Xiufang C, Da-Wen S, Zhigljavsky A, Zilinskas A. Stochastic Global Optimization. 2001;(4):1–262.
25.
Zitzler E, Thiele L. Multiobjective evolutionary algorithms: A comparative case study and the Strength Pareto approach. IEEE Transactions on Evolutionary Computation. 1999;(4):257–71.
26.
Deb K, Saxena D. Proc. of 2006 IEEE Congress on Evolutionary Computation. 2006;3353–60.
27.
Abakarov A, Nuñez M. Thermal food processing optimization: algorithms and software. Journal of Food Engineering. 2012;
28.
Abakarov A, Sushkov Y, Almonacid S, Simpson R. Multiobjective Optimization Approach: Thermal Food Processing. Journal of Food Science. 2009;(9):471-E487.
29.
Azarpazhooh E, Ramaswamy H. Modeling and Optimization of Microwave Osmotic Dehydration of Apple Cylinders Under Continuous-Flow Spray Mode Processing Conditions. Food and Bioprocess Technology. 2012;(5):1486–501.
30.
Barbosa-Cánovas G, Vega-Mercado H. Physical, chemical, and microbiological characteristics of dehydrated foods. 1996;29–99.
31.
Belton V, Stewart T. Multiple criteria decision analysis: an integrated approach. 2002;
32.
Beuthe M, Scannella G. Comparative analysis of UTA multicriteria methods. European Journal of Operational Research. 2001;(2):246–62.
33.
Bevilacqua M, ’amore D, Polonara A, F. A multi-criteria decision approach to choosing the optimal blanchingfreezing system. Journal of Food Engineering. 2004;(3):253–63.
34.
Brockhoff D, Zitzler E. Objective Reduction in Evolutionary Multiobjective Optimization: Theory and Applications. Evolutionary Computation. 2009;(2):135–66.
35.
Carmone F, Kara A, Zanakis S. A Monte Carlo investigation of incomplete pairwise comparison matrices in AHP. European Journal of Operational Research. 1997;(3):538–53.
36.
Costa C, Chagas M. 12th Mini Euro Confer-ence. European Journal of Operational Research. 2004;(2):323–31.
37.
Deb K. Multi-objective optimization using evolutionary algorithms. Wiley-Interscience series in systems and optimization. 2001;
38.
Abakarov A. Paper presented at 11th International Congress on Engineering and Food. 2011;1525–6.
39.
Del Castillo E. Process optimization: a statistical approach. 2007;
40.
Derringer G, Suich R. Simultaneousoptimization of Several Response Variables. Journal of Food Engineering. 1980;(4):214–9.
41.
Derringer G. A Balancing Act -Optimizing a Products Properties. Quality Progress. 1994;(6):51–8.
42.
Erdogdu F. Optimization in Food Engineering. Journal of Food Engineering. 2003;(4):1–777.
43.
Eren I, Kaymak-Ertekin F. Optimization of osmotic dehydration of potato using response surface methodology. Journal of Food Engineering. 2007;(1):344–52.
44.
Multiple Criteria Decision Analysis: State of the Art Surveys. 2005;1–1085.
45.
Fogliatto F, Albin S. An AHP-based procedure for sensory data collection and analysis in quality and reliability applica-tions. Food Quality and Preference. 2003;(5–6):375–85.
46.
Goñi S, Salvadori V. Proceedings of the 11th International Congress on Engineering and Food. Paper presented at 11th International Congress on Engineering and Food. 2011;1425.
47.
Goñi S, Salvadori V. Modelbased multi-objective optimization of beef roasting. Journal of Food Engineering. 2012;(1):92–101.
48.
Grandzol J. Improving the faculty selection process in higher education: a case for the analytic hierarchy process. IR Applications. 2005;(6):1–13.
49.
Hadiyanto H, Boom R, Van Straten G, Boxtel V, Esveld A, D. Journal of Food Engineering. 2009;(5):709–29.

Citation

Copyright

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Article metrics

Google scholar: See link

The statements, opinions and data contained in the journal are solely those of the individual authors and contributors and not of the publisher and the editor(s). We stay neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Most read articles

Indexed by
Scopus
DOAJ
Sherpa-Romero
Google Scholar
Crossref