@inproceedings{af04360998a5468091d1f468728be471,
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}",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 3rd International Conference on Computing Measurement Control and Sensor Network, CMCSN 2016 ; Conference date: 20-05-2016 Through 22-05-2016",
year = "2017",
month = aug,
day = "10",
doi = "10.1109/CMCSN.2016.29",
language = "English",
series = "Proceedings - 2016 3rd International Conference on Computing Measurement Control and Sensor Network, CMCSN 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "68--71",
editor = "Pei-Wei Tsai and Junzo Watada and Naoyuki Kubota",
booktitle = "Proceedings - 2016 3rd International Conference on Computing Measurement Control and Sensor Network, CMCSN 2016",
address = "United States",
}