Thermal processing optimization through a modified adaptive random search

Abakarov, A.; Sushkov, Yu. A.; Almonacid, Sergio; Simpson, Ricardo

doi:10.1016/j.jfoodeng.2009.01.013

Cited by 19 publications

(6 citation statements)

References 32 publications

(35 reference statements)

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“…The authors developed a hybrid algorithm for kinetics modelling based on the Adaptive Random Search Method (ARSM) enhanced by the Genetic Algorithms (GA) theory. The ARSM was used in practical implementations to find the global minimum for a function on a compact set (Abakarov et al, 2009). To enhance optimisation methods, combinations of different algorithms are frequently tested.…”

Section: Co 2 Reduction Mitigation Capture and Sequestrationmentioning

confidence: 99%

Recent cleaner production advances in process monitoring and optimisation

Klemeš

Varbanov

Huisingh

2012

Journal of Cleaner Production

143

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Section: Co 2 Reduction Mitigation Capture and Sequestrationmentioning

confidence: 99%

Recent cleaner production advances in process monitoring and optimisation

Klemeš

Varbanov

Huisingh

2012

Journal of Cleaner Production

143

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“…The multiobjective optimization approach used in this study is based on optimizing the following aggregating functions by using the adaptive random search method (Sushkov 1969; Abakarov and Sushkov 2002; Simpson and others 2008; Abakarov and others 2009).…”

Section: Methodsmentioning

confidence: 99%

Multiobjective Optimization Approach: Thermal Food Processing

Abakarov¹,

Sushkov²,

Almonacid³

et al. 2009

Journal of Food Science

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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.

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“…Computer aidedengineering have significantly helped during the last decades in optimal control problems of food processing. Thermal processing function is an important food preservation method to inactivate bacterial spores of public health significance as well as food spoilage microorganisms in sealed containers of food, using heat treatments at temperatures well above the ambient boiling point of water in pressurized steam retorts (autoclaves) that are not detrimental to food quality and underutilize plant capacity (Simpson et al, 2003;Holdsworth and Simpson, 2007;Abakarov et al, 2009).…”

Section: Application Of Evolutionary Algorithms In Food Processingmentioning

confidence: 99%

Food processing optimization using evolutionary algorithms

Enitan¹,

Adeyemo²

2011

Afr. J. Biotechnol.

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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.

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Thermal processing optimization through a modified adaptive random search

Cited by 19 publications

References 32 publications

Recent cleaner production advances in process monitoring and optimisation

Recent cleaner production advances in process monitoring and optimisation

Multiobjective Optimization Approach: Thermal Food Processing

Food processing optimization using evolutionary algorithms

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