Diversity-enhanced particle swarm optimizer and its application to optimal flow control of sewer networks
- Authors
- Beak, H.; Kim, T.-H.; Ryu, J.; Oh, J.
- Issue Date
- Oct-2013
- Citation
- Proceedings of 2013 Science and Information Conference, SAI 2013, v.SAI 2013, pp 977 - 978
- Pages
- 2
- Journal Title
- Proceedings of 2013 Science and Information Conference, SAI 2013
- Volume
- SAI 2013
- Start Page
- 977
- End Page
- 978
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/48871
- ISSN
- 0000-0000
- Abstract
- This study proposes a novel diversity-enhanced Particle Swarm Optimization (PSO) scheme for optimal control of overflow in multi-reservoir sewer networks. To this aim, first two diversity boosting methodologies, cyclic neighborhood-based learning mechanism and three-phase velocity control mechanism for the particle's behavior, are proposed, and then these are combined with the constrained PSO method. Next, the linearized mathematical models of the components composing sewer networks with storage facilities are presented, and then the corresponding formulation suitable for a model predictive control (MPC) technique is discussed. Finally, the developed PSO scheme is applied to this MPC problem for minimizing the total overflow in sewer networks under a certain external inflow scenario. © 2013 The Science and Information Organization.
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Collections - College of Engineering > School of Mechanical Engineering > 1. Journal Articles
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