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GA Optimization of Coconut Sugar Cooking Process: A Preliminary Study using Stochastic Universal Sampling (SUS) Technique

Published: 18 February 2017 Publication History

Abstract

This study presents the optimization of cooking process for the coconut sugar. Designing the process control of cooking coconut sugar requires dynamic programming that uses nonlinear differential equations which could be difficult to model and analyze. The development of the optimization process will make use of genetic algorithm (GA) based approach using stochastic universal sampling as its selection process. The developed system will be incorporated for the automation of coconut sugar production. Factors associated in the drying of coconut sap like treatment time and color of the honey were considered in this study.

References

[1]
D. B. Masa, "Coco sugar: current processing technologies, utilization and recommended practices," Retrieved 25 January 2016 from Coconut Development Board (CDB), India website: http://www.coconutboard.nic.in.
[2]
T. P. Trinidad, "Health benefits from coco sap-based products," Food and Nutrition Research Institute, Department of Science and Technology. Retrieved 25 January 2016 from Philippine Coconut Authority website: http://www.pca.da.gov.ph.
[3]
"Coconut sap sugar industry roadmap," 1st Nat'l. Coconut Sap Sugar Congress, Marco Polo Hotel, Davao City, Philippines, 2012.
[4]
K. McCall, "Genetic algorithms for modelling and optimization," Journal of Computational and Applied Mathematics," vol. 184, issue 1, pp. 205--222, December 1, 2005.
[5]
L. Sheng, L. Gao-yun, S. Jia and S. Tian-ying, "Research on optimization efficiency of genetic algorithms," 2nd Int'l. Symp, on Systems and Control in Aerospace and Astronautics, pp. 1--4, December 10-12 2008.
[6]
M. P. Kumar and S. Vijayachitra, "Process optimization using genetic algorithm," Int'l. Conf. on Control, Automation, Communication and Energy Conversion (INCACEC), pp. 1--6, 2009.
[7]
J. M. Johnson and Y. Rahmat-Samii, "Genetic algorithm optimization and its application to antenna design," Antennas and Propagation Society International Symposium, 1994.
[8]
S. M. Elsayed, R. A. Sarker and D. L. Essam, "Improved genetic algorithm for constrained optimization," 2011 Int'l. Conf. on Computer Engineering & Systems (ICCES), pp. 111--115, 2011.
[9]
W. F. Punch, M. Pei, L. Chia-Shun, E. D. Goodman, P. Hovland, and R. Enbody, "Further research on feature selection and classification using genetic algorithms", 5th Int'l. Conf. on Genetic Algorithm, Champaign IL, pp 557--564, 1993.
[10]
W. Siedlecki and J. Sklansky, "A note on genetic algorithms for large-scale feature selection," Pattern Recognition Letters, Vol. 10, pp. 335--347, 1989.
[11]
L. I. Kuncheva and L. C. Jain, "Designing classifier fusion systems by genetic algorithms," IEEE Trans. on Evolutionary Computation, Vol. 33, pp 351--373, 2000.
[12]
Muhlenbein and D. Schlierkamp-Voosen, "Predictive models for the breeder genetic algorithm," Continuous Parameter Optimization, Evolutionary Computation, Vol. 1 (1), pp. 25--49, 1993.
[13]
R. O. Duda, P. E. Hart, P.E. and D. G. Stork, "Pattern classification, 2nd Edition," John Wiley & Sons, Inc., New York NY., 2001.

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cover image ACM Other conferences
ICCAE '17: Proceedings of the 9th International Conference on Computer and Automation Engineering
February 2017
365 pages
ISBN:9781450348096
DOI:10.1145/3057039
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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  • Macquarie U., Austarlia

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 February 2017

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Author Tags

  1. coconut sugar
  2. genetic algorithm
  3. optimal control
  4. stochastic universal sampling

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Cited By

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  • (2024)Research on High Voltage Circuit Breaker Multi-Sensor Signal Feature Selection Method Based on GA-Kmeans AlgorithmEngineering Research Express10.1088/2631-8695/ad82a9Online publication date: 2-Oct-2024
  • (2023)Automated Cooking Systems: Benefits, Challenges, and Future Directions2023 IEEE 15th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM)10.1109/HNICEM60674.2023.10589209(1-6)Online publication date: 19-Nov-2023
  • (2021)Optimization of Biofilter Size for Aquaponics Using Genetic AlgorithmJournal of Advanced Computational Intelligence and Intelligent Informatics10.20965/jaciii.2021.p063225:5(632-638)Online publication date: 20-Sep-2021
  • (2021)An Optimization Framework for Image Contouring of Handwriting Recognition using Genetic Algorithm2021 IEEE 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM)10.1109/HNICEM54116.2021.9732027(1-4)Online publication date: 28-Nov-2021
  • (2020)Improving Just-in-Time Delivery Performance of IoT-Enabled Flexible Manufacturing Systems with AGV Based Material TransportationSensors10.3390/s2021633320:21(6333)Online publication date: 6-Nov-2020
  • (2019)Optimization of Nonlinear Temperature Gradient on Eigenfrequency Using Genetic Algorithm for Reinforced Concrete Bridge Structural HealthWorld Congress on Engineering and Technology; Innovation and its Sustainability 201810.1007/978-3-030-20904-9_11(141-151)Online publication date: 9-Aug-2019
  • (2017)Image preprocessing using quick color averaging approach for color machine vision (CMV) systems2017IEEE 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM)10.1109/HNICEM.2017.8269475(1-4)Online publication date: Dec-2017

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