Standard

Thermal processing optimization through a modified adaptive random search. / Abakarov, A.; Sushkov, Yu.; Almonacid, S.; Simpson, R.

In: Journal of Food Engineering, Vol. 93, No. 2, 2009, p. 200-209.

Research output: Contribution to journal › Article

Harvard

Abakarov, A, Sushkov, Y, Almonacid, S & Simpson, R 2009, 'Thermal processing optimization through a modified adaptive random search', Journal of Food Engineering, vol. 93, no. 2, pp. 200-209. https://doi.org/doi:10.1016/j.jfoodeng.2009.01.013

APA

Abakarov, A., Sushkov, Y., Almonacid, S., & Simpson, R. (2009). Thermal processing optimization through a modified adaptive random search. Journal of Food Engineering, 93(2), 200-209. https://doi.org/doi:10.1016/j.jfoodeng.2009.01.013

Vancouver

Abakarov A, Sushkov Y, Almonacid S, Simpson R. Thermal processing optimization through a modified adaptive random search. Journal of Food Engineering. 2009;93(2):200-209. https://doi.org/doi:10.1016/j.jfoodeng.2009.01.013

Author

Abakarov, A. ; Sushkov, Yu. ; Almonacid, S. ; Simpson, R. / Thermal processing optimization through a modified adaptive random search. In: Journal of Food Engineering. 2009 ; Vol. 93, No. 2. pp. 200-209.

BibTeX

@article{8299a62b129a4771bfe2e32c31e6c5e9,
title = "Thermal processing optimization through a modified adaptive random search",
abstract = "This research suggests a modification of the adaptive random search method. The proposed modification is based on the utilization of the well-known logistic function or logistic curve in order to improve the random search adaptation characteristics. The algorithm tested results show the advantage of the random search modification over the previous random search organization, especially in the case of solving the multi-modal optimization problems. An interesting and important food industry optimization problem, such as thermal processing, was solved by the new organization of adaptive random search.",
keywords = "Global optimization, Thermal processing, Random search, Logistic curve",
author = "A. Abakarov and Yu. Sushkov and S. Almonacid and R. Simpson",
year = "2009",
doi = "doi:10.1016/j.jfoodeng.2009.01.013",
language = "English",
volume = "93",
pages = "200--209",
journal = "Journal of Food Engineering",
issn = "0260-8774",
publisher = "Elsevier",
number = "2",

}

RIS

TY - JOUR

T1 - Thermal processing optimization through a modified adaptive random search

AU - Abakarov, A.

AU - Sushkov, Yu.

AU - Almonacid, S.

AU - Simpson, R.

PY - 2009

Y1 - 2009

N2 - This research suggests a modification of the adaptive random search method. The proposed modification is based on the utilization of the well-known logistic function or logistic curve in order to improve the random search adaptation characteristics. The algorithm tested results show the advantage of the random search modification over the previous random search organization, especially in the case of solving the multi-modal optimization problems. An interesting and important food industry optimization problem, such as thermal processing, was solved by the new organization of adaptive random search.

AB - This research suggests a modification of the adaptive random search method. The proposed modification is based on the utilization of the well-known logistic function or logistic curve in order to improve the random search adaptation characteristics. The algorithm tested results show the advantage of the random search modification over the previous random search organization, especially in the case of solving the multi-modal optimization problems. An interesting and important food industry optimization problem, such as thermal processing, was solved by the new organization of adaptive random search.

KW - Global optimization

KW - Thermal processing

KW - Random search

KW - Logistic curve

U2 - doi:10.1016/j.jfoodeng.2009.01.013

DO - doi:10.1016/j.jfoodeng.2009.01.013

M3 - Article

VL - 93

SP - 200

EP - 209

JO - Journal of Food Engineering

JF - Journal of Food Engineering

SN - 0260-8774

IS - 2

ER -

ID: 5222048