@inproceedings{68d1b7e74c774dd9984d83354c33c32b,
title = "The extraordinary particle swarm optimization and its application in constrained engineering problems",
abstract = "The particle swarm optimization (PSO) is a natural-inspire optimization algorithm mimicking the movement behavior of animal flocks for food searching. Although the algorithm presents some advantages and widely application, however, there are several drawbacks such as trapping in local optima and immature convergence rate. To overcome these disadvantages, many improved versions of PSO have been proposed. One of the latest variants is the extraordinary particle swarm optimization (EPSO). The particles in the EPSO are assigned to move toward their own determined target through the search space. The applicability of EPSO is verified by several experiments in engineering optimization problems. The application results show the outperformance of the EPSO than the other PSO variants in terms of solution searching and as well as convergence rate.",
keywords = "Engineering optimization problem, Extraordinary particle swarm optimization, Urban drainage system",
author = "Ngo, {Thi Thuy} and Ali Sadollah and Yoo, {Do Guen} and Choo, {Yeon Moon} and Jun, {Sang Hoon} and Kim, {Joong Hoon}",
note = "Publisher Copyright: {\textcopyright} Springer Nature Singapore Pte Ltd. 2017. Copyright: Copyright 2017 Elsevier B.V., All rights reserved.; Proceedings of the 3rd International Conference on Harmony Search Algorithm, ICHSA 2017 ; Conference date: 22-02-2017 Through 24-02-2017",
year = "2017",
doi = "10.1007/978-981-10-3728-3_5",
language = "English",
isbn = "9789811037276",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
pages = "35--41",
editor = "{Del Ser}, Javier",
booktitle = "Harmony Search Algorithm - Proceedings of the 3rd International Conference on Harmony Search Algorithm (ICHSA 2017)",
}