Comparative Study on Recent Development of Heuristic Optimization Methods

Van Oanh Sai, Chin Shiuh Shieh, Yuh Chung Lin, Mong Fong Horng, Trong The Nguyen, Quang Duy Le, Jung Yi Jiang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

In engineering and design problems, various noisy non-linear mathematical optimization problems can't be efficaciously solved by using conventional optimization techniques. But metaheuristic algorithms seem very efficient to approach in these problems and became very popular such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO). Recently, many new metaheuristic algorithms were proposed, but the performance of these algorithms in solving noisy non-linear optimization problems when compared with popular methods still need more of verifications. In this context, two popular algorithms called GA and PSO will be compared with some recent metaheuristic algorithms such as Grey Wolf Optimizer, Firefly Algorithm, and Brain Storm Optimization algorithm in finding optimal solutions of noisy non-linear optimization problems. The results will be compared in terms of accuracy of the best solutions found and the execution time.

Original languageEnglish
Title of host publicationProceedings - 2016 3rd International Conference on Computing Measurement Control and Sensor Network, CMCSN 2016
EditorsPei-Wei Tsai, Junzo Watada, Naoyuki Kubota
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages68-71
Number of pages4
ISBN (Electronic)9781509010936
DOIs
Publication statusPublished - 2017 Aug 10
Event3rd International Conference on Computing Measurement Control and Sensor Network, CMCSN 2016 - Matsue, Shimane, Japan
Duration: 2016 May 202016 May 22

Publication series

NameProceedings - 2016 3rd International Conference on Computing Measurement Control and Sensor Network, CMCSN 2016

Other

Other3rd International Conference on Computing Measurement Control and Sensor Network, CMCSN 2016
CountryJapan
CityMatsue, Shimane
Period16-05-2016-05-22

Fingerprint

optimization
genetic algorithms
Particle swarm optimization (PSO)
Genetic algorithms
fireflies
wolves
Heuristics
Comparative study
brain
Brain
engineering
Optimization problem
Metaheuristics
Genetic algorithm
Particle swarm optimization
Nonlinear optimization

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Signal Processing
  • Information Systems and Management
  • Instrumentation
  • Information Systems

Cite this

Sai, V. O., Shieh, C. S., Lin, Y. C., Horng, M. F., Nguyen, T. T., Le, Q. D., & Jiang, J. Y. (2017). Comparative Study on Recent Development of Heuristic Optimization Methods. In P-W. Tsai, J. Watada, & N. Kubota (Eds.), Proceedings - 2016 3rd International Conference on Computing Measurement Control and Sensor Network, CMCSN 2016 (pp. 68-71). [8008642] (Proceedings - 2016 3rd International Conference on Computing Measurement Control and Sensor Network, CMCSN 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CMCSN.2016.29
Sai, Van Oanh ; Shieh, Chin Shiuh ; Lin, Yuh Chung ; Horng, Mong Fong ; Nguyen, Trong The ; Le, Quang Duy ; Jiang, Jung Yi. / Comparative Study on Recent Development of Heuristic Optimization Methods. Proceedings - 2016 3rd International Conference on Computing Measurement Control and Sensor Network, CMCSN 2016. editor / Pei-Wei Tsai ; Junzo Watada ; Naoyuki Kubota. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 68-71 (Proceedings - 2016 3rd International Conference on Computing Measurement Control and Sensor Network, CMCSN 2016).
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title = "Comparative Study on Recent Development of Heuristic Optimization Methods",
abstract = "In engineering and design problems, various noisy non-linear mathematical optimization problems can't be efficaciously solved by using conventional optimization techniques. But metaheuristic algorithms seem very efficient to approach in these problems and became very popular such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO). Recently, many new metaheuristic algorithms were proposed, but the performance of these algorithms in solving noisy non-linear optimization problems when compared with popular methods still need more of verifications. In this context, two popular algorithms called GA and PSO will be compared with some recent metaheuristic algorithms such as Grey Wolf Optimizer, Firefly Algorithm, and Brain Storm Optimization algorithm in finding optimal solutions of noisy non-linear optimization problems. The results will be compared in terms of accuracy of the best solutions found and the execution time.",
author = "Sai, {Van Oanh} and Shieh, {Chin Shiuh} and Lin, {Yuh Chung} and Horng, {Mong Fong} and Nguyen, {Trong The} and Le, {Quang Duy} and Jiang, {Jung Yi}",
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Sai, VO, Shieh, CS, Lin, YC, Horng, MF, Nguyen, TT, Le, QD & Jiang, JY 2017, Comparative Study on Recent Development of Heuristic Optimization Methods. in P-W Tsai, J Watada & N Kubota (eds), Proceedings - 2016 3rd International Conference on Computing Measurement Control and Sensor Network, CMCSN 2016., 8008642, Proceedings - 2016 3rd International Conference on Computing Measurement Control and Sensor Network, CMCSN 2016, Institute of Electrical and Electronics Engineers Inc., pp. 68-71, 3rd International Conference on Computing Measurement Control and Sensor Network, CMCSN 2016, Matsue, Shimane, Japan, 16-05-20. https://doi.org/10.1109/CMCSN.2016.29

Comparative Study on Recent Development of Heuristic Optimization Methods. / Sai, Van Oanh; Shieh, Chin Shiuh; Lin, Yuh Chung; Horng, Mong Fong; Nguyen, Trong The; Le, Quang Duy; Jiang, Jung Yi.

Proceedings - 2016 3rd International Conference on Computing Measurement Control and Sensor Network, CMCSN 2016. ed. / Pei-Wei Tsai; Junzo Watada; Naoyuki Kubota. Institute of Electrical and Electronics Engineers Inc., 2017. p. 68-71 8008642 (Proceedings - 2016 3rd International Conference on Computing Measurement Control and Sensor Network, CMCSN 2016).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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T1 - Comparative Study on Recent Development of Heuristic Optimization Methods

AU - Sai, Van Oanh

AU - Shieh, Chin Shiuh

AU - Lin, Yuh Chung

AU - Horng, Mong Fong

AU - Nguyen, Trong The

AU - Le, Quang Duy

AU - Jiang, Jung Yi

PY - 2017/8/10

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N2 - In engineering and design problems, various noisy non-linear mathematical optimization problems can't be efficaciously solved by using conventional optimization techniques. But metaheuristic algorithms seem very efficient to approach in these problems and became very popular such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO). Recently, many new metaheuristic algorithms were proposed, but the performance of these algorithms in solving noisy non-linear optimization problems when compared with popular methods still need more of verifications. In this context, two popular algorithms called GA and PSO will be compared with some recent metaheuristic algorithms such as Grey Wolf Optimizer, Firefly Algorithm, and Brain Storm Optimization algorithm in finding optimal solutions of noisy non-linear optimization problems. The results will be compared in terms of accuracy of the best solutions found and the execution time.

AB - In engineering and design problems, various noisy non-linear mathematical optimization problems can't be efficaciously solved by using conventional optimization techniques. But metaheuristic algorithms seem very efficient to approach in these problems and became very popular such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO). Recently, many new metaheuristic algorithms were proposed, but the performance of these algorithms in solving noisy non-linear optimization problems when compared with popular methods still need more of verifications. In this context, two popular algorithms called GA and PSO will be compared with some recent metaheuristic algorithms such as Grey Wolf Optimizer, Firefly Algorithm, and Brain Storm Optimization algorithm in finding optimal solutions of noisy non-linear optimization problems. The results will be compared in terms of accuracy of the best solutions found and the execution time.

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M3 - Conference contribution

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BT - Proceedings - 2016 3rd International Conference on Computing Measurement Control and Sensor Network, CMCSN 2016

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PB - Institute of Electrical and Electronics Engineers Inc.

ER -

Sai VO, Shieh CS, Lin YC, Horng MF, Nguyen TT, Le QD et al. Comparative Study on Recent Development of Heuristic Optimization Methods. In Tsai P-W, Watada J, Kubota N, editors, Proceedings - 2016 3rd International Conference on Computing Measurement Control and Sensor Network, CMCSN 2016. Institute of Electrical and Electronics Engineers Inc. 2017. p. 68-71. 8008642. (Proceedings - 2016 3rd International Conference on Computing Measurement Control and Sensor Network, CMCSN 2016). https://doi.org/10.1109/CMCSN.2016.29